{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "960ceacb-3c3f-484c-95b9-172bd009b1a4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a generic code for drawing a state's Home Districts for neutral map estimation\n",
      "In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\n"
     ]
    }
   ],
   "source": [
    "#  THIS IS THE PRIMARY VERSION TO USE FOR ALL STATES  #See MO for orig 2/10/24\n",
    "print(\"This is a generic code for drawing a state's Home Districts for neutral map estimation\") #Jan'24\n",
    "print(\"In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\")\n",
    "import shapely\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "from shapely.ops import nearest_points, transform\n",
    "from shapely.affinity import translate, scale\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "from scipy.optimize import minimize, minimize_scalar\n",
    "import math\n",
    "import time\n",
    "import ast\n",
    "# from HDmethods import *   #I want to implement this, but my HDmethods require shapely functions\n",
    "# see https://stackoverflow.com/questions/66877728/proper-way-to-use-import-when-calling-external-function for a future workaround\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)         \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2ab4a3d5-f4e7-4aec-b81c-0e786cd35b57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def getWeightedAvgAndSD(LIST, WEIGHTS):\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def squish(shapeList, cutLINE, farLINE, newFarLINE):\n",
    "    \"\"\"\n",
    "    This method compresses a list of shapes lying between the cutLINE and the farLINE)\n",
    "    such that the Polygons now lie between the cutLINE and the newFarLINE, which is closer to the cutLINE\n",
    "    Used to compress state outcroppings into a more compact state representation.\n",
    "     (I tried doing this point by point (see #'s), but this overdistorted geometries.)\n",
    "      (#This was a manual alternative to shapely.affinity.scale and .translate operations)\n",
    "       So instead, we run this AFTER established untransformed map topology, and \n",
    "        we simply scale and translate each unit.  This loses true connectivity.\n",
    "        Scaling is all lengths scale by compression of distance\n",
    "    The cut, far, and newFar LineString segments are preferably parallel\n",
    "    The method returns the modified shapes of all pollys\n",
    "    \"\"\"\n",
    "    if cutLINE.intersects(farLINE) or cutLINE.intersects(newFarLINE):\n",
    "        print(\"cutLine,farLine, newFarLine were\",cutLINE, farLINE, newFarLINE)\n",
    "        raise Exception(\"ERROR: the proposed cutLine intersects the current or proposed far line\")\n",
    "    newPollys = list()\n",
    "    for polly in shapeList:\n",
    "        pollyCP = polly.centroid\n",
    "        cutPt =     nearest_points(cutLINE,   pollyCP)[0]\n",
    "        farPt =     nearest_points(farLINE,   pollyCP)[0]\n",
    "        newFarPt =  nearest_points(newFarLINE,pollyCP)[0]\n",
    "        curr_cutX, curr_cutY =            pollyCP.x - cutPt.x, pollyCP.y -  cutPt.y\n",
    "        currFar_CutX , currFar_CutY  =    farPt.x - cutPt.x, farPt.y   -  cutPt.y\n",
    "        new_currFarX, new_currFarY =      newFarPt.x - farPt.x, newFarPt.y - farPt.y\n",
    "        newFar_CutX,  newFar_CutY =       newFarPt.x - cutPt.x, newFarPt.y   -  cutPt.y\n",
    "        distanceRatio = newFarPt.distance(cutPt)/farPt.distance(cutPt) #scale area ^length^2\n",
    "        XOFF,YOFF = 0., 0.\n",
    "        XFACT, YFACT = 1., 1.  #default = no stretch\n",
    "        # basic equation: (new-cut)/(curr-cut) = (newFar-cut)/(currFar - cut)\n",
    "        #  or: (new-curr)  = (curr-cut)*(newFar-currFar)/(currFar - cut)   # -1 to both sides\n",
    "        if currFar_CutX != 0:\n",
    "            XOFF =  curr_cutX * new_currFarX / currFar_CutX\n",
    "            XFACT =              newFar_CutX / currFar_CutX\n",
    "        if currFar_CutY != 0:\n",
    "            YOFF =  curr_cutY * new_currFarY / currFar_CutY\n",
    "            YFACT =              newFar_CutY / currFar_CutY\n",
    "        newPolly = translate(polly,xoff=XOFF,yoff=YOFF)\n",
    "        newPolly = scale(newPolly, xfact=XFACT, yfact=YFACT, origin='centroid')\n",
    "        newPollys.append( newPolly )       \n",
    "    return newPollys\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "#  The below four methods are TO SNAP to HD SHAPES without any solving / iteration\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def buildPoly(CP, RADII, ANGLES):  #reconstructs a full polygon from four HD wedges emanating from the centerpoint\n",
    "    Pt = [Point(0,0)]*8\n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW]  #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ]\n",
    "        Pt[nW*2] =   Point(CP.x + RADII[nW]*math.cos(ccwAngle), CP.y + RADII[nW]*math.sin(ccwAngle) )\n",
    "        Pt[nW*2+1] = Point(CP.x + RADII[nW]*math.cos( cwAngle), CP.y + RADII[nW]*math.sin( cwAngle) )        \n",
    "    POLLY = Polygon([Pt[0],Pt[1],Pt[2],Pt[3],Pt[4],Pt[5],Pt[6],Pt[7] ])\n",
    "    return POLLY\n",
    "\n",
    "def getPolyPop(POLLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points contained by a polygon\n",
    "    WPOP, WLIST = 0., list()\n",
    "    for tt in CANDIDATELIST:\n",
    "        if POLLY.contains(TRACTCP[tt]):\n",
    "            WPOP += TRACTPOP[tt]\n",
    "            WLIST.append(tt)\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonCPP(POLLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county in getPolyPop\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if POLLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonHCunits(POLLY, HC, UNITLIST, UNITCP, UNITPOP, ALLFUSEDCOUNTIES, AREAFRAC, COUNTYGEOM, \n",
    "                  NEIGHBORCOUNTYLIST, COUNTYUNITLIST):\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"unit counties\" are added as whole units if a sufficient area fraction is captured.  For non-unitCs, we probe each component vtd / tract\n",
    "    \"\"\"\n",
    "    UPOP, ULIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county before we called this method\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        #1/9/24 - NEED TO MODIFY THE ORDER BELOW TO AVOID CREATING HOLES AND ENCLAVES ########################\n",
    "        \n",
    "        for c in latestClist:\n",
    "            for cc in list( set(NEIGHBORCOUNTYLIST[c]).difference(set(ALLFUSEDCOUNTIES)) ):\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        if cc+0.5 in UNITLIST:\n",
    "                            if POLLY.intersection(COUNTYGEOM[cc]).area >=  AREAFRAC[cc] * COUNTYGEOM[cc].area :\n",
    "                                intersectedClist.append(cc)   #for unit counties, intersections only count if they capture sufficient area\n",
    "                                newClist.append(cc)\n",
    "                                UPOP += UNITPOP[UNITLIST.index(cc+0.5)]\n",
    "                                ULIST.append( UNITLIST.index(cc+0.5) )\n",
    "                        else:                           \n",
    "                            intersectedClist.append(cc)\n",
    "                            newClist.append(cc)\n",
    "                            if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                                unitsToAdd = COUNTYUNITLIST[cc]\n",
    "                                UPOP += np.sum(  [ UNITPOP[uu] for uu in unitsToAdd ]  )\n",
    "                                ULIST += unitsToAdd\n",
    "                            else:\n",
    "                                for uu in COUNTYUNITLIST[cc]:\n",
    "                                    if POLLY.contains(UNITCP[uu]):\n",
    "                                        UPOP += UNITPOP[uu]\n",
    "                                        ULIST.append(uu)\n",
    "        latestClist = newClist.copy()\n",
    "        \n",
    "    return UPOP, ULIST\n",
    "\n",
    "def clusterSwell(CP_, CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, TGTPOP):\n",
    "    \"\"\"\n",
    "    This method grows a Home District by \"swelling\" from a corner county cluster.  First, we add the full cluster,\n",
    "     then we add closest neighbor units to the home district centerpoint CP_ until we reach the TGTPOP\n",
    "     \"\"\"\n",
    "    #global borderUnits\n",
    "    hd_CCBdist = [CP_.distance(geo) for geo in CCBgeom]\n",
    "    CCBno = hd_CCBdist.index(np.min(hd_CCBdist))  #ID's the closest cluster to this HD center.  Should contain the HD, but rarely will not\n",
    "    unitNo = allUnits.index(CCBno+0.25)\n",
    "    newList, prevList, addedList, addedPop = [unitNo], [unitNo], [unitNo], unitPop[unitNo]  #seed with the cluster pop and unit\n",
    "    while addedPop < 0.99 * TGTPOP and len(newList) > 0:\n",
    "        trySet = set(list())\n",
    "        for U in addedList:\n",
    "            trySet = trySet.union(set(unitNbrs[U] ) )\n",
    "        tryList = list( trySet.difference(set(addedList)) )\n",
    "        tryDist = [ CP_.distance(unitCP[UU]) for UU in tryList ]\n",
    "        idx = np.argsort(tryDist)\n",
    "        idxNo, newList = 0, list()\n",
    "        haveNotAdded = True\n",
    "        while idxNo < len(tryList) and haveNotAdded:\n",
    "            UU = tryList[idx[idxNo]]\n",
    "            if unitPop[UU] + addedPop < 1.01 * TGTPOP and wontEnclave(UU, addedList, unitNbrs, borderUnits) :\n",
    "                newList.append(UU)\n",
    "                addedList.append(UU)\n",
    "                addedPop += unitPop[UU]\n",
    "                haveNotAdded = False\n",
    "            idxNo +=1\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    return addedPop, addedList\n",
    "            \n",
    "def getFakeHC(HDPOLLY, HC, CCBlist, countyGeom, MAP) :\n",
    "    \"\"\"\n",
    "    This method is for setting a fake home county for counties in corner clusters, so that county neighbors can be found budding from the \"home county\"\n",
    "    We pick the county in the cluster closest to the map center and intersecting the HDpoly.  This will be an active county on the cluster boundary   \n",
    "    \"\"\"\n",
    "    MAPcenter = MAP.centroid\n",
    "    for L in CCBlist:\n",
    "        if HC in L:\n",
    "            distList, cList = list(), list()\n",
    "            for C in L:\n",
    "                if HDPOLLY.intersects(countyGeom[C]):\n",
    "                    distList.append(countyGeom[C].distance(MAPcenter))\n",
    "                    cList.append(C)\n",
    "    fakeHC = cList[distList.index(np.min(distList)) ]\n",
    "    return fakeHC\n",
    "\n",
    "def getLongDist(CP1, CP2, xScale = 1.0): #distance between two points with EW distance scaled down by latitude\n",
    "    #LAT = MAP.centroid.y\n",
    "    #xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "    dist = ( xScale*xScale * (CP1.x - CP2.x)*(CP1.x - CP2.x)  +  (CP1.y - CP2.y)*(CP1.y - CP2.y) ) **0.5 \n",
    "    return dist\n",
    "\n",
    "# THESE ARE THE METHODS USED IN SOLVING HD SHAPES\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def getCountyWP(T, WEDGEPOLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points in a wedge excluding a point\n",
    "        WPOP, WLIST = 0., list()\n",
    "        for tt in CANDIDATELIST:\n",
    "            if tt != T and WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                WPOP += TRACTPOP[tt]\n",
    "                WLIST.append(tt)\n",
    "        return WPOP, WLIST\n",
    "\n",
    "def getNonCWP(WEDGEPOLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by an infinite polygonal wedge for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def isIncludedA(STARTa, ENDa, TESTa): #determines if a test angle is between a start and end angle (True)\n",
    "    \"\"\"\n",
    "    The start angle must be less than the end angle when placed on the [0, 2 pi] interval  (ccw convention)\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    STARTa, ENDa, TESTa = STARTa % (2.*pi), ENDa % (2.*pi), TESTa % (2.*pi)  #place on the 2pi interval\n",
    "    isIncludedA = False\n",
    "    if STARTa  > ENDa :  #included angle straddles east\n",
    "        if   TESTa  >= STARTa or TESTa < ENDa :  #near-east between the two\n",
    "            isIncludedA = True\n",
    "    else:\n",
    "        if TESTa >= STARTa and TESTa < ENDa :  #normal case\n",
    "            isIncludedA = True\n",
    "    return isIncludedA\n",
    "\n",
    "def getNonCWP_c(STARTANGL, ENDANGL, HC, TRACTCP,TRACTPOP,COUNTYGEOM,COUNTYPOP,COUNTYTRACTLIST,\n",
    "                                    NEIGHBORCOUNTYLIST, UUDIST, UUANGLE, WEDGEPOLY) :\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a polygonal wedge for counties contiguous with the Home County (no hop-overs),\n",
    "    EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    Unlike its getNonCWP vanilla parent, this one uses angles rather than infinite wedges for units (still wedges for counties)\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if isIncludedA(STARTANGL, ENDANGL, UUANGLE[tt]): #WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getExitAngle(CP,WEDGEPOLY, MAP, A0, A1):\n",
    "    \"\"\"\n",
    "    This code determines the orientation angle from a CenterPoint to the intersection of a wedge with an exterior boundary\n",
    "    If an intersection is not found, we just take the average angle of the wedge start/stop angles A0, A1 as this orientation angle\n",
    "    MAP must be a single polygon for this to work in the revised code (tho could run thru all polygons in MAP if a multipolygon)\n",
    "    \"\"\"\n",
    "    EXITANGLE = 0.5* (A0 + A1) #this will be the angle from the x-axis to the exit beeline\n",
    "    if WEDGEPOLY.intersects(MAP.exterior):\n",
    "        edgeLine = WEDGEPOLY.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "        closePoint = nearest_points(edgeLine,CP)[0]\n",
    "        dx = closePoint.x - CP.x       #this and below lines were indented in original code***\n",
    "        dy = closePoint.y - CP.y\n",
    "        EXITANGLE =  pi/2. * np.sign(dy)  #default in case dx=0\n",
    "        if (dx != 0. ):\n",
    "            EXITANGLE = math.atan(dy/dx) + random.uniform(-0.01,0.01) #add wiggle to avoid exact NESW orientation in gridded states\n",
    "            if dx < 0. :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                EXITANGLE = pi + EXITANGLE\n",
    "    return EXITANGLE # this reorients 0th wedge to face boundary's closest point\n",
    "\n",
    "def getNewAngles(mWP, tWP, ADP, LEVEL_L, MINADJRATIO, MAXANGLE, MAXANGLERATIO, nUNFILLEDWEDGES): \n",
    "    \"\"\"\n",
    "    This method classifies Home Districts based on how their post-reoriented equi-angle max wedge pops stack up vs targets,\n",
    "     then changes wedge angles in some situations to pick up more population along the boundary\n",
    "    If there is one wedge that will fall short of a quarter district pop, then we adjust angles if it is sufficiently short    \n",
    "    (Using \"HD2\" code, the opposite wedge's pop will be constrained as well.)\n",
    "    If there are two opposite-facing constrained wedges, we do not adjust angles\n",
    "    If there are two adjacent constrained wedges, we classify as a corner (no angle change) if the adjacent wedge is sufficiently constrained,\n",
    "      otherwise we treat as a single constrained wedge\n",
    "    If there are three constrained wedges, the angles are unchanged; we use the 4th wedge to pick up all pop\n",
    "    If all four wedges are constrained, there is an error and we raise a flag.\n",
    "    mWP is the quadlist of maxWedgePops we would get by extending each wedge to the MAP boundary\n",
    "    tWP is the quadlist of targetWedgePops\n",
    "    LEVEL_L is the non-dimensional distance to the boundary at which we no longer adjust wedge angles to drive more near-boundary pop\n",
    "    MAXANGLERATIO is the max ratio of the wide angle (facing the boundary) to the normal angle (e.g. 90deg for four wedges) ...\n",
    "    but this is truncated near-boundary to MAXANGLE (e.g. 1.8 pi/2 instead of increasing all the way to 1.9 pi/2)\n",
    "      NOTE THAT this code does not consider nearly-shorted wedges -- those are a separate method called later if all mWP's > tWP's\n",
    "    \"\"\"   \n",
    "    isChange = False   #default; we are NOT changing angles\n",
    "    printDebuggg = False\n",
    "    NWEDGES = len(mWP)\n",
    "    avgWedgeAngle = 2.*math.pi / NWEDGES\n",
    "    minW = mWP.index(np.min(mWP))  #index of the wedge with the lowest max wedge pop\n",
    "    oppW = int( int(minW + NWEDGES/2) % NWEDGES )  #and its opposing wedge\n",
    "    Lstar = ( mWP[minW] / (0.25*ADP) )**0.5  #shortest wedge's nondim'l distance to boundary\n",
    "    \n",
    "    case = \"keep same wedge angles\" #default; no unfillable wedges or all but one are unfillable\n",
    "    if nUNFILLEDWEDGES >= NWEDGES:\n",
    "        raise Exception(\"ERROR! ALL WEDGES ARE CONSTRAINED for tract\",t,\".  IMPOSSIBLE!!\")\n",
    "    if nUNFILLEDWEDGES == 1:\n",
    "        case = \"constrain opp wedge\"\n",
    "        if Lstar >= levelL :\n",
    "            case = \"keep same wedge angles\"  #not close enough to boundary to distort HD shape\n",
    "    if nUNFILLEDWEDGES == 0 or nUNFILLEDWEDGES == NWEDGES - 1:  #far from boundary or with only one wedge w/large pop\n",
    "        case = \"keep same wedge angles\"   \n",
    "    if nUNFILLEDWEDGES == 2:  #must determine if opposite or adjacent           \n",
    "        if mWP[oppW] < tWP[oppW]:  #shorted wedges oppose each other, so ...\n",
    "            case = \"keep same wedge angles\" #...the HD shape will naturally widen to pick up adjacent pop\n",
    "        else:  #we have 2 adjacent (non-opposing) shorted wedges... but how shorted?  ID the adjacent wedge\n",
    "            for nW in range(NWEDGES):\n",
    "                if mWP[nW] < tWP[nW] and nW != minW :\n",
    "                    adjW = nW  #this is the adjacent wedge\n",
    "                    adjRatio = mWP[adjW] / tWP[adjW]\n",
    "            if adjRatio < minAdjRatio:  #we're close to a corner (this adjacentWedge is significantly constrained)\n",
    "                case = \"keep same wedge angles\"\n",
    "                if printDebuggg :\n",
    "                    print(\"Not adjusting wedge angles for tract\",t,\"as 2nd-sparsest wedge\",adjW,\"has pop\",mWP[adjW] )\n",
    "            else:\n",
    "                case = \"constrain opp wedge\"  #we will set the angles and target pops as if the adj wedge were not constrained\n",
    "    \n",
    "    if case == \"keep same wedge angles\":\n",
    "        isChange = False\n",
    "        WEDGEANGLE = [avgWedgeAngle for w in range(NWEDGES) ]\n",
    "\n",
    "    if case == \"constrain opp wedge\":  #Here, we modify wedge angles.  MWP's will be recalc'd outside the method\n",
    "        isChange = True  \n",
    "        wideAngle = min(MAXANGLE, avgWedgeAngle*max(  1,( 1.+(MAXANGLERATIO-1.)*(LEVEL_L - Lstar)/(LEVEL_L - 0.) )  ) )\n",
    "        WEDGEANGLE = [(2.*pi - 2. * wideAngle)/ (NWEDGES - 2.) for w in range(NWEDGES) ]  \n",
    "        WEDGEANGLE[minW] = wideAngle\n",
    "        WEDGEANGLE[oppW] = wideAngle\n",
    "    \n",
    "    return isChange, WEDGEANGLE\n",
    "\n",
    "def rebalanceTWPs(MWP, TWP, BARREDLIST=list()):\n",
    "    \"\"\"\n",
    "    This method iteratively increases targetWedgePops to accommodate wedges that have maxWedgePop < targetWedgePop.\n",
    "    The wedgePop gap is distributed equally among wedges that have some capacity and are not BARRED (e.g. an opposite wedge in HD2 method)\n",
    "     (If this pushes some wedges over capacity, this will be fixed in a later run through loop inside this method)\n",
    "    We also flag which wedges \"will fill\" = have sufficient capacity after the rebalancing of the targets to not use the entire maxWedgePoly\n",
    "    \"\"\"\n",
    "    DEBUGrTWP = False\n",
    "    NWEDGES = len(MWP)\n",
    "    unorderedCapacity = [MWP[w] - TWP[w] for w in range(NWEDGES) ]\n",
    "    idx = np.argsort(unorderedCapacity)\n",
    "    #for nn in range(NWEDGES):\n",
    "    #    print(MWP[idx[nn]])\n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        for nn in range(NWEDGES):\n",
    "            print(\"barred list, orig MWP, TWP\",BARREDLIST, r3(MWP[nn]),r3(TWP[nn]) )\n",
    "    \n",
    "    for nn in range(NWEDGES):  #going from least to most maxWedgePop here ...\n",
    "        nW = idx[nn]\n",
    "        if MWP[nW] < TWP[nW]: #need to redistribute extra target to higher-capacity wedges ...\n",
    "            wedgePopGap = TWP[nW] - MWP[nW]\n",
    "            TWP[nW] = MWP[nW]  #max out this wedge\n",
    "            nReceivers = 0.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....\n",
    "                    nReceivers += 1.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....                    \n",
    "                    TWP[WW] += wedgePopGap / nReceivers  #... so give it equal share of the gap, even if this goes over; we'll correct in later loop\n",
    "                    \n",
    "    WILLFILL = [1]*NWEDGES\n",
    "    for nW in range(NWEDGES):\n",
    "        if MWP[nW] < 1.001* TWP[nW]:  #required pop nearly or truly requires the entire wedge\n",
    "            WILLFILL[nW] = 0 \n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        print(\"adjusted TWP's are\",TWP)\n",
    "    return TWP, WILLFILL\n",
    "\n",
    "def solveWedge(nontractTWP,t, hC, STARTANGLE, ENDANGLE, MAXD, TOLERPOPS, tractCP, tractPop,\n",
    "               countyTractList, countyGeom, countyPop, neighborCountyLIST,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    #### NO LONGER USED; SEE FASTER SOLVEWEDGEB BASED ON UNIT-UNIT DISTANCES  *********\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop (which excludes the home tractPop)\n",
    "    The wedge has a fixed starting and ending angle.  Its maximum diameter is angle-related to max diameter of the state map\n",
    "    It uses bisection, NOT scipy minimize to minimize the square error in the wedge pop vs. target\n",
    "    The method passes back the final wedge pop and list of tracts in the wedge\n",
    "    \"\"\"\n",
    "    chgLoopNo, maxLoopNo = 10., 22.  #when we will start relaxing the pop tolerance, and when we give up\n",
    "    includedAngl = ENDANGLE - STARTANGLE\n",
    "    guessedR = MAXD / math.cos(0.5*includedAngl)  #max possible wedge radius, accounting for possible wide angle\n",
    "    popTol = TOLERPOPS[0]  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    #                      We loosen toward half the MAX tractPop if not converging\n",
    "    \n",
    "    offsetPop = 88888888.  #to force a reduction the first time through the loop\n",
    "    dr = guessedR\n",
    "    loopNo = 0\n",
    "    while abs(offsetPop) > popTol and loopNo < maxLoopNo:\n",
    "        loopNo +=1\n",
    "        popTol = max(TOLERPOPS[0], TOLERPOPS[0] + (TOLERPOPS[1] - TOLERPOPS[0]) * (loopNo - chgLoopNo) / (maxLoopNo - chgLoopNo) )\n",
    "        dr = 0.5*dr\n",
    "        guessedR -= dr*np.sign(offsetPop)\n",
    "        \n",
    "        guessedPoly = buildWedge(tractCP[t],STARTANGLE, ENDANGLE, guessedR,XSCALE) \n",
    "        iCP, iClist =  getCountyWP(t,guessedPoly, tractCP, tractPop, countyTractList[hC])\n",
    "        nonCP, nonClist = getNonCWP(guessedPoly, hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyLIST)\n",
    "        offsetPop = iCP + nonCP - nontractTWP\n",
    "        #print(t,loopNo,r5(guessedR),int(iCP),int(nonCP),r3(offsetPop+nontractTWP),r3(nontractTWP),\"t,loop,R,iCP,nonCP,pop,target\")\n",
    "        if loopNo >= maxLoopNo-1:\n",
    "            print(\"WARNING. Looped\",loopNo,\"times for t,angles,R\",t,r3(STARTANGLE),r3(ENDANGLE),r5(guessedR),\n",
    "                  \"wedgePop offset, target are\",int(offsetPop), int(nontractTWP) )    \n",
    "    finalPop = iCP + nonCP\n",
    "    finalList = iClist + nonClist\n",
    "    return finalPop, finalList, guessedR, loopNo\n",
    "\n",
    "#above = bisection.  Below solveWedgeB uses static unit-unit distances\n",
    "# Also tried scipy minimize, which doesn't seem any faster\n",
    "\n",
    "def solveWedgeB(nontractTWP,T, HC, POLLY, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that intersect,\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2x2 array\n",
    "    \"\"\"\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    \n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList = 0, 0, list()\n",
    "    notFull = True\n",
    "    while notFull :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist    \n",
    "\n",
    "def solveWedgeC(nontractTWP,T, HC, POLLY, STARTANGL, ENDANGL, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST, UUANGLE):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that\n",
    "    fall within the angle range (in lieu of wedgeB's check for intersection),\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2D array\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    STARTANGL, ENDANGL = STARTANGL % (2.*pi), ENDANGL % (2.*pi)\n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList, latestDist = 0, 0, list(), 0.00001  #dummy value\n",
    "    notFull = True\n",
    "    while notFull and i < len(UUDIST) - 2 :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if isIncludedA(STARTANGL, ENDANGL, UUANGLE[TT]) : #POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist \n",
    "\n",
    "\n",
    "def getPartialTract(t, HDTRACTLIST, offsetPop, UUDIST, tractPop, neighborLIST):\n",
    "    \"\"\"\n",
    "    If offsetPop is >0, this method identifies the tract with centroid farthest from Home t that can jettison at least offsetPop ...\n",
    "    ... by slicing out part of this tract.\n",
    "    If offsetPop <0, we ID a tract CLOSEST to Home t among neighbors of in-HD tracts to pick up a partial\n",
    "    We return the tractID and its new partial use\n",
    "    We have updated this method to pass the uuDist slice for tract t instead of computing tract distances inside here\n",
    "    \"\"\"\n",
    "    debugGPT = False\n",
    "    NTRACTS = len(tractCP)\n",
    "    bigDist = 9999999.\n",
    "    qualifyingTractList = list()\n",
    "    isWholeTract = False\n",
    "    if offsetPop > 0:\n",
    "        homeDist = [0.]*NTRACTS  #default = 0 to not get picked\n",
    "        for TT in HDTRACTLIST:\n",
    "            if tractPop[TT] > offsetPop:\n",
    "                qualifyingTractList.append(TT)\n",
    "        for TT in qualifyingTractList:\n",
    "            homeDist[TT] = UUDIST[TT]\n",
    "        if len(qualifyingTractList) == 0:  #very rare case where all in-HD tracts are too small.  Jettison nearly the whole farthest one\n",
    "            isWholeTract = True\n",
    "            for TT in HDTRACTLIST:\n",
    "                if tractPop[TT] > 0.9*np.average(tractPop): #set arbitrary min qualifying pop\n",
    "                    homeDist[TT] = UUDIST[TT]\n",
    "        targetT = homeDist.index(np.max(homeDist))\n",
    "        partialUseFrac = max(0.0001,(tractPop[targetT] - offsetPop)/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(\"positive offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    else: #pick up a partial\n",
    "        homeDist = [bigDist]*NTRACTS\n",
    "        for TT in HDTRACTLIST:\n",
    "            for TTT in neighborList[TT]:\n",
    "                if TTT not in qualifyingTractList and TTT not in HDTRACTLIST and tractPop[TTT] > abs(offsetPop):\n",
    "                    qualifyingTractList.append(TTT)\n",
    "        for TTT in qualifyingTractList:\n",
    "            homeDist[TTT] = UUDIST[TTT]\n",
    "        if len(qualifyingTractList) == 0 :  #rare case where most nearby tracts are small.  Add nearly the whole biggest one\n",
    "            isWholeTract = True\n",
    "            maxPop = 0.\n",
    "            targetT = -999\n",
    "            for TT in HDTRACTLIST:\n",
    "                for TTT in neighborList[TT]:\n",
    "                    if TTT not in qualifyingTractList and TTT not in HDTRACTLIST : # we'll take just one, even if doesn't fill gap\n",
    "                        qualifyingTractList.append(TTT)\n",
    "            for TTT in qualifyingTractList:\n",
    "                if tractPop[TTT] > maxPop:\n",
    "                    targetT = TTT\n",
    "                    maxPop = tractPop[targetT]\n",
    "        else:\n",
    "            targetT = homeDist.index(np.min(homeDist))\n",
    "        partialUseFrac = min(0.9999, -1.* offsetPop/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(t,\"'s negative offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    \n",
    "    return targetT, partialUseFrac\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    smallPieceList = foundList.copy()\n",
    "    if len(foundList) < len(VLIST):\n",
    "        isUnbroken  = False\n",
    "        if len(foundList) > 0.5*len(VLIST): #return a contiguous sub-list that is guaranteed to have at most half the total units in the list\n",
    "            smallPieceStarter = list( set(VLIST).difference(set(foundList) ) )[0]\n",
    "            smallPieceList = getContigFromStarter(smallPieceStarter, VLIST, NEIGHBORLIST)\n",
    "    return isUnbroken, smallPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS):\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "    \"\"\"\n",
    "    ADJLIST =              getAdjoiners(UNITLIST, UNITNBRS)\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(set(UNITLIST)) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(get2nbrs(UNITLIST,UNITNBRS), UNITNBRS)  #in case adjoiners are only queen-adjacent\n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eLists = list()\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    couldBeEnclaved = list(  set([i for i,L in enumerate(UNITNBRS)]).difference( set(UNITLIST + offmapList) )  )  \n",
    "    allAdjoiners = getAdjoiners(UNITLIST, UNITNBRS)\n",
    "    isContig, shortList = isContiguous(allAdjoiners,UNITNBRS) #quicker than contig check on entire complement\n",
    "    starter = shortList[0]\n",
    "    while not isContig:\n",
    "        newEnclaveList = getContigFromStarter(starter,couldBeEnclaved, UNITNBRS)\n",
    "        eLists.append(newEnclaveList)\n",
    "        couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )\n",
    "        isContig, shortList = isContiguous(couldBeEnclaved,UNITNBRS)    #this will kick out before writing the final sublist, which is the map majority\n",
    "        starter = shortList[0]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, dummy = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary\n",
    "        wontEnclave, dummy = isContiguous(adjoiners,NBRLIST)\n",
    "    return wontEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d041d328-83e0-45db-a869-e0956c23ee26",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the state postal code; e.g. OH  CO\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, enter 1 below to use co_pl2020_vtd.dbf as this state's population data file\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "  1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempting to read in state unit geometries.  Stand by ...\n",
      "I read in the Census popn data. CO has 5773714 peeps and is divided into 3108 shapes.\n"
     ]
    }
   ],
   "source": [
    "STATE = str(input(\"Enter the state postal code; e.g. OH \")).upper()\n",
    "popFilename = STATE.lower()+\"_pl2020_vtd.dbf\"\n",
    "print(\"OK, enter 1 below to use\",popFilename,\"as this state's population data file\")\n",
    "enter1 = input(\" \")\n",
    "if int(enter1) != 1:\n",
    "    popFilename = input(\"OK, then enter the pop data file.  Typically a xx_pl2020_vtd.dbf\")\n",
    "print(\"attempting to read in state unit geometries.  Stand by ...\")\n",
    "tractPopFile = gpd.read_file(\"state_map_files/\"+popFilename)\n",
    "trueTractGeom = tractPopFile['geometry']\n",
    "nTracts = len(trueTractGeom)\n",
    "tractPop = tractPopFile['P0010001']\n",
    "statePop = np.sum(tractPop)\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "print(\"I read in the Census popn data.\",STATE,\"has\",statePop,\"peeps and is divided into\",nTracts,\"shapes.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3bfdea9d-b0ea-497a-a556-6b488a3e333e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the number of districts in the state.  My guess is 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 64 counties in CO .  I will assign them county Nos 0 - 63\n"
     ]
    }
   ],
   "source": [
    "tractGeom = trueTractGeom.copy()   #for some states, we will modify geom, so preserve original\n",
    "#tractNAME20 = tractPopFile['NAME20']\n",
    "tractPop = tractPopFile['P0010001']\n",
    "inputfileCountyNo = tractPopFile['COUNTYFP20']\n",
    "vtdGEOID20 =  tractPopFile['GEOID20'] \n",
    "nDistricts = int(round(statePop/760000,0))\n",
    "nCutDistricts = 0\n",
    "nDistricts = int(input(\"Enter the number of districts in the state.  My guess is \"+str(nDistricts)))\n",
    "tractArea = [tractGeom[t].area for t in range(nTracts)]\n",
    "trueTractCP =   [tractGeom[t].centroid for t in range(nTracts)]\n",
    "tractCP = trueTractCP.copy()  #for some states, we move secluded corners into the map, so save the true data\n",
    "tractCPx =  [tractCP[t].x for t in range(nTracts)]\n",
    "tractCPy =  [tractCP[t].y for t in range(nTracts)]\n",
    "inputCountyNumbers = list()\n",
    "for t in range(nTracts):\n",
    "    if inputfileCountyNo[t] not in inputCountyNumbers:\n",
    "        inputCountyNumbers.append(inputfileCountyNo[t])\n",
    "nCounties = len(inputCountyNumbers)\n",
    "print(\"There appear to be\",nCounties,\"counties in\",STATE,\".  I will assign them county Nos 0 -\",int(nCounties-1))\n",
    "sortedICNs = list(np.sort(inputCountyNumbers))\n",
    "countyNo = [sortedICNs.index(inputfileCountyNo[t]) for t in range(nTracts) ]\n",
    "\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c9c54b60-b12d-407e-812d-e26e1a6bbe1a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPECIAL FOR CO - REASSIGN SOME VTD'S TO ADJACENT COUNTIES FOR BETTER CONTIGUITY\n"
     ]
    }
   ],
   "source": [
    "print(\"SPECIAL FOR CO - REASSIGN SOME VTD'S TO ADJACENT COUNTIES FOR BETTER CONTIGUITY\")\n",
    "intList = [1888, 1918, 2015, 2062, 2196,2214,2215,2217] \n",
    "envC = 16\n",
    "for v in intList:\n",
    "    countyNo[v] = envC\n",
    "intList = [2634]\n",
    "envC = 16\n",
    "for v in intList:\n",
    "    countyNo[v] = envC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "adffc7a4-a78c-477f-8ea4-7f8e5109fa2a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now build the county-by-county geometries, hoping there are no islands\n",
      "Building county geom for county 0\n",
      "Building county geom for county 20\n",
      "Building county geom for county 40\n",
      "Building county geom for county 60\n",
      "Here is your original county-base map before any triage; e.g eliminating coastal unpopulated tracts w pop < 4.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 0 unpopulated coastal tracts.  Lets plot them and their parent counties\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"We will now build the county-by-county geometries, hoping there are no islands\")\n",
    "skipList = list()  #a list of units we previously know to skip in the map\n",
    "isAlteredCounty = [False for c in range(nCounties)]\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "countyPop =       [0. for c in range(nCounties)]\n",
    "countyGeom =      [dummyPoly for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    if t not in skipList:\n",
    "        c = countyNo[t]\n",
    "        countyTractList[c].append(t)\n",
    "        countyPop[c] += tractPop[t]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Building county geom for county\",c)\n",
    "    for t in countyTractList[c]:\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            countyGeom[c] = tractGeom[t]\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "origMAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    origMAP = origMAP.union(countyGeom[c])\n",
    "    if countyGeom[c] == dummyPoly:\n",
    "        print(\"WARNING! county\",c,\"is empty!\")\n",
    "    else:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "minTractPop = 4.5\n",
    "print(\"Here is your original county-base map before any triage; e.g eliminating coastal unpopulated tracts w pop <\",minTractPop)\n",
    "plt.show()\n",
    "for c in range(nCounties):\n",
    "    for t in countyTractList[c]:\n",
    "        if tractPop[t] < minTractPop:\n",
    "            if tractGeom[t].intersects(origMAP.exterior):\n",
    "                isAlteredCounty[c] = True\n",
    "                skipList.append(t)\n",
    "print(\"There appear to be\",len(skipList),\"unpopulated coastal tracts.  Lets plot them and their parent counties\")\n",
    "for t in skipList:\n",
    "    plotPoly(tractGeom[t])\n",
    "    plotCenter(t,tractGeom[t])\n",
    "plotPoly(origMAP,0.2)\n",
    "for c in range(nCounties):\n",
    "    if isAlteredCounty[c]:\n",
    "        plotPoly(countyGeom[c])\n",
    "plt.show()\n",
    "trueMAP = origMAP  #use these terms interchangeably"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cef6999e-8920-4aa6-bb3b-54a1f122db3d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "confirming we have a clean boundary for counties 0 and 16\n"
     ]
    },
    {
     "data": {
      "image/png": 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/HTOcEy+8uMOP2x4xFh+HRTS82ySoEULEphicfM/2+ynzHeL8R3+D6XAGgo6aYMS2a24tC3dC4lHLOuvWm0I6Zu0xbMtGWxa2bWFbNT+2ha5ZfqH+/bX10DpQL2wdqF9NXcdrzUx7XJPbFy79hAOHi9t5pjqWHQ39KiIkEtQIIWKTjt1E2NqZgJVSKGWCYWKG7ViBYxiGCU5nmI5Sx/n5l2E/RmvFYKNf2OgIv++kRU0IEZtisKUm2BUUY89LxAilmuoR7VQS1AghYlJr1kDqKnTNFUPWbOpctpbJ90JhqMjP6SPvDCFEbIrBPIi6oCaWL7DR+dxk8NPRGUpF/G3XqqBm4cKFjB8/npSUFFJSUpg+fTpvvfVWcHtBQQFXXnkl2dnZJCQkcM4557Bly5YWy/T5fNxzzz0MGTKEuLg4JkyYwJIlSxrt98gjjzBo0CDi4uKYPHkyn3zySWuqLoTobmJxxrQYbH1qWqQvjQ3ZUVafaKXoYi01/fr144EHHiA3N5fc3FxOO+00LrzwQtavX4/WmlmzZrF9+3Zee+01Vq1axYABAzjjjDOoqKhotsy5c+fy2GOP8de//pUNGzZw/fXXc9FFF7Fq1argPv/5z3/4+c9/zp133smqVas48cQTmTlzJnl5eW1/5kKI2BaDq1BrbUs3SAREOvm1qzC6Wk7NBRdcwLnnnsvw4cMZPnw4999/P0lJSSxfvpwtW7awfPlyFi5cyNSpUxkxYgSPPPII5eXlPP/8882W+eyzz3LHHXdw7rnnMnjwYG644QbOPvts/vSnPwX3WbBgAddccw3XXnsto0aN4qGHHiInJ4eFCxe2/ZkLIWKaVeLBrvRHuhodqruuPC66CNXk1Emdqs1Dui3L4oUXXqCiooLp06fj8XgAiIurmwnSNE1cLhfLli3j2muvbbIcj8fT4DEA8fHxLFu2DACv18vKlSu57bbbGuxz1lln8dlnn7VYR4/HE6wXQGlpaehPUAjRpel4i5Lda1GlgSHJSilQZqCNXFtg1NxvGKCMmlsVmPVW1d2nDCOQUKEIBBTKqBnmrFCmAYZZU05tWWAYDgiWXTNrbm0d2vOctC0xTQTYMdiTGQ6GUhHvfmp1ULN27VqmT59OdXU1SUlJvPLKK4wePRqfz8eAAQO4/fbbeeyxx0hMTGTBggXs37+f/Pz8Zss7++yzWbBgASeddBJDhgzh/fff57XXXsOyLAAOHjyIZVn06tWrweN69erF/v37W6zr/Pnz+e1vf9vapyiEiAFV6VtRysblzERrG3RgMjgApV1oApO+adsfmEHXr8G2oXYWXU3gfm0FUjxqJ9bVGm1r0DX71Ewoh61rjhPYJ/C7rvmdwP4qUKZ3QyU9vjuBtIFjW/ekdAyOUz+CrRQf79nPN395CI3G1gobTeBUamwNplK4DIVLKdyGwmUYgVvTJM4wcDlM4kwTt8PEdDgwHc6aHweGw0FSegaDj5naqnrFWE9mWBgq8tlQrQ5qRowYwerVqykuLuall17iiiuu4KOPPmL06NG89NJLXHPNNWRkZGCaJmeccQYzZ85ssbyHH36Y6667jpEjR6KUYsiQIVx11VU89dRTDfY78htOKH2ct99+O7fcckvw99LSUnJyclr5jIUQXZEybRL6DSQhYUCkqxLkKT1M/tvv0HvODBJ7t75eOhaTn4/w/XGj+GrLNpShMAh89gduwUBhKPBrjcfWeG2bKltT7PPj1eDTPrwavFrjA3zQYMbj2pmX83y9GZFn4nS5alruGtej/l2VXj+zJ/brjKffpakoGNLd6qDG5XIxdOhQAKZMmcKKFSt4+OGHeeyxx5g8eTKrV6+mpKQEr9dLZmYm06ZNY8qUKc2Wl5mZyauvvkp1dTVFRUVkZ2dz2223MWjQIAB69uyJaZqNWmUKCwsbtd4cye1243a7W/sUhRAxINBVEz2zVpTv3sHBL1bQ74Jv4YiLb1MZ2tYxnyg87cyZTDszfOXvWL2Su//vv/z5xItI7tEzfAfqhgyl0B2/VFjr6tDeArTWDfJWAFJTU8nMzGTLli3k5uZy4YUXHrWcuLg4+vbti9/v56WXXgo+xuVyMXnyZN59990G+7/77rscf/zx7a2+ECJmRccy3bZlk//BuxRvXk3/b1/c5oAmQEs/SHvVtiTIaQwLHeEOqFa11Nxxxx3MnDmTnJwcysrKWLRoEUuXLg3OK/PCCy+QmZlJ//79Wbt2LTfddBOzZs3irLPOCpZx+eWX07dvX+bPnw/AF198wd69e5k4cSJ79+7l7rvvxrZtfvWrXwUfc8sttzBnzhymTJnC9OnTefzxx8nLy+P666/viHMghIhBWlsRHYZbWVrC3q+/wNq6B8fQXrgzhrJv8yaMmuRjoyaxOPB/o9H/G24P/N/v9cZ8S024yazM4RNIFI5sHVoV1BQUFDBnzhzy8/NJTU1l/PjxLFmyhDPPDLQV5ufnc8stt1BQUECfPn24/PLLmTdvXoMy8vLyMIy6F1N1dTVz585l+/btJCUlce655/Lss8+SlpYW3Of73/8+RUVF3HPPPeTn5zN27FjefPNNBgyInr5yIUR00diBxR4j5OP//AXH/v1U5vVAL9sBLK+39cjApKUrQcN9lVsuxu0RTBaXYWQdLhpGPymtIz2qvPOUlpaSmppKSUkJKSkpka6OECKMCgrfIi11Cm53ZkSOv3jhr6muKuTMOb/Htm20bWFbNbd2YMRUbeJq4/9b2LrefVbdY1KzepM9fGREnlMs2LpiOfc+9goLF9xBQkpqpKsTU95cm8/UgRlkJnd8Lmuo1+82z1MjhBBRLcKJwhob0+EiJTMrYnUQjUlLTfgYqq57L2J1iOjRhRAiTAI5NZH8iLNl9t9oVJsnLDk1YdDFFrQUQoiuQwORy6lBa5R8xEadYEuNjCLrcEYUzFMj7zghREyK9OgnraWlJhrVdY/I36ajqSgY/SRBjRAiJkV69JMm9ifK64q0LS014SI5NUIIES7aJpIfcRo7sICmiCp189RIUNPRDKUivkq3BDVCiJgU6URh1Q0Wn+yKZPK9MJKcGiGECI/A2k/S/SSOUBvUSPdTh5OWGiGECBNNhLuftJYujigkLTXho5CWGiGECJvIjn6ykI/Y6FObKCyNaB1PqZYX/OgM8o4TQogwUACGJApHG2mpCZ9o6G6Vv6oQQoSB1hYq0l9bRSOyTEJ4SU6NEELEIqVRhnzERhtta5BWmrCIhjhR/rJCiBgV2a+MWoZ0RykdFRff2CWJwkIIEQYRvnJpLXkbUUjbEtSESzScVnnHCSFEGER6SLlomta2LDQaw+QvK4QQYSHz1EQjrTVa/i5hI4nCQggRi7QkpEYjbeuo6CaJSVFwYh2RroAQQoRDpOfM0NgRr4OA/Vs3s/rTTzFNhdM0Kdi2ObCctAiLSM9iIEGNECIm6Uh/vEqicFR4+423+d+Wcvq4fNhaY2sHU7Ldka5WTIqGIF6CGiGECAsJaqKBZWuO6aG4857fRLoq3YLk1AghRAwKtBRF/ptrd2fLwqKdJhpOswQ1QggRDtpGKVn7KdJsW0sKTTciQY0QQoSBVjo6vrp2c7aWdZ46U6Rz2SSoEUKIcJBJ3qKC1tJS01mi4TTLO04IIcJFrqYRZ2swpKWm00iisBBCxCCZjj86aGwMCS47RTR088k7TgghwkKjDPmIjTRbUps6lbTUCCFETNKg5WoaaYHRT/J36AzRcJpl8j0hhAgLjTJkSHc42JZF6YFClKFQholhGBimiap/awRubVvjMKPgais6hQQ1QggRFjKjcLi89/xzPPnJVtyW56j7ljmSmDk0qRNqJSDyQ7olqBFCiDDQskp32BSXVTAgEX581aVoy8LWNrZlo22r7ta2sS0L27LIGT020lXuFqKhPUyCGiGECAtZpTtcbK1xut0MGDcx0lURR4h0orAENUIchc/nY9u2bSQlBZqwmxq22Nr7HA4HcXFxaK0D3yhrfiwr8A1T16xXU7+M2v8rpTAMgx49eoT8HHQznzTN3d/SvrV11lof9SfU/Y7c1zRN+vbt264hohUVW/H5Smp+U02UpWp+NFrbaO3H4UjCMFxtPuaRpPspPGxb5p6JRtHwJ5GgRoijWLVqFX369EEpFbzo1tdUYHC0+8rLy/F4AvkAplmT6FjzY5pmo2PVf6zWmoMHD7Jt27ZWPY/WBAjN7VsbaLX0YxhGSPsd+Zja562UorKyknXr1jFu3LhWPcf6sjLPpqjoI6jp4w/29QfPZd05VcqBUgYeTyH9+1/d5mPWp7ElqAkT27alDUw0SYIaIUKQk5MT6So0MHjw4EhXIeyWL1/ersdnZBzf6sfs3vMsllWFaca369hB0fDVNQZpWc9JNEO+RgghopJpmliW1anHzMqaSWHhWx1UmrTUhIutNTKvYTSKfKApLwshRFTq2bMnBw8e7NRjul098foOdVBpGqVknppwsLXGiIILqGgs0onCEtQIcRStSaYVHad3797s37+/04+bmDiUioqtHVCSzM8fLrat5dRGoWj4m0hQI0QLtm7ditvtjnQ1uqX4+Hiqq6s7/bgZ6Sdw6PBn7S5HazCkpSYsbMmpiVqRnnxPghohmqG1Zvfu3UyYMCHSVRGdyDCcaN0BuTzalgtvmNhaIwtvR6dIz80kQY0Qzfjmm28YNWqUXJgiKFLn3u3KwuMpaFcZGqKjPT4GBVrB5NxGm2joqZegRogjlJaWsnnzZnbt2kXv3r0jXZ1uLVL5TBkZJ3Do0KftK6RmAkXR8bS2paUmKkU+10nmqRGinsLCQrZu3crIkSPJzs6OdHVEhDidafj8JUff8SgkqAkPW1pqRDOkpUaIGpZlsWnTJqZPn05GRkZwWQQROZEMCgzlxLa9bX68joKWGq01Dz74IIMHDyY+Pp4JEybw4osvRrROHcHWGiVNNVEnGrqfpKVGiBpbt25l9OjREb8QieiQmjqZ4pKVZKRPb1sBmojn1MydO5eXX36ZhQsXMmzYMD7++GNmz55NZmYmJ598ckTr1h621jJLTZSK9MenBDVC1Dh48CAjRoyIdDVElEhKGsnuPf9se1CDjuiMwhUVFSxYsIAPPviA6dMDz2Hw4MEsW7aMxx57rEsHNVqDIS01UUcT+dFPEtQIUcPlcuH1enG5Om6VZtF1tbfFTke4i2TDhg1UV1dz5plnNrjf6/UyadKkCNWqY9ha44h0k4BoRLqfhIgi6enplJaW0rNnz0hXRUSJOHc21dX7iItra9J45C68tm0DsHjxYvr27dtgW1efUFIShaNXpP8sEtQIUcPlcuHz+SJdDdEG1T6Lsmo/cU4DQylcDgOn2f6un4yM4yksXEJ29ndb/dhIt9SMHj0at9tNXl5el+5qaoq2dcS7OURj0bCkjAQ1QtTw+XwkJCREuhqiDf61fBfZafFUeS1srfFaNvuKq/jl2SPbVa7DkYzfKm/bg3VkL7zJycnceuut3Hzzzdi2zYwZMygtLeWzzz4jKSmJK664ImJ1ay8bLTk1USgKcuMlqBHdl23brFu3Dtu20Vqzf/9+ZsyYEelqiTZwOQzOHdenwX3PfL6zQ8o2DDeW5cE0W9dlo4n8sON7772XrKws5s+fz/bt20lLS+OYY47hjjvuiGi92ktrLfORRKlIt6BJUCO6LZ/Ph8fjYfz48SilGDt2LE6nM9LVEm0Qzo/RtNQpFJesoEdG6wJerYno6CcIJDvfeOON3HjjjRGtR0eztZKWmigUBb1PEtSI7mvt2rUMGjSoyydNdgdaa7QmuP6v1oG1gAP3abxW409Tn6UpqarJkdINVw+uHdlUmwOgUKDqms4PV3ip8llYtsays6gu+bzVQY1CRzJPOKYFFrSUkxtttCyTIETkZGZmsn37dtauXcu4ceNk1FMUenJ1GZusnUBNfKDqGreVCgQjhoLM5MaB6aT+aSz9prDJcu2afJf6H8D1v2XGOQ3SE1yYhkIpxVub4jl2TOj1DgZLEW6piVWB2ZojXQvRlEj/WSSoEd3WgAEDGDBgAHv37sXj8US6OqIJfZMdXD59YJsee0z/dI7pn94h9fhik0GVt4p4V3xI+2sdGE4d8U/4GGVrMAwJGKNOFHQ/yatCdGt+v5/ly5cTFxcX6aqIKNa/Rw92FOwK/QE1H+7SUhMetrTURK1I/13kHSe6tb179zJ9+nR69OgR6aqIKNY3owd7Dx0Ief/alhpZRyw8tEy+F5VqM9QiSYIa0a3t2bOH3r17R7oaIsqlJqRQUlkZ8v7ars2pkQtvONjI2k/RKBpGP7UqqFm4cCHjx48nJSWFlJQUpk+fzltvvRXcXlBQwJVXXkl2djYJCQmcc845bNmy5ajlPvTQQ4wYMYL4+HhycnK4+eabqa6uDm6/++67UUo1+JELkWivr7/+mpycHOmbj2JR8BkJgNnK2YlrR1pJUBMe2paWmmgV6T9LqxKF+/XrxwMPPMDQoUMBePrpp7nwwgtZtWoVo0ePZtasWTidTl577TVSUlJYsGABZ5xxBhs2bCAxMbHJMp977jluu+02nnzySY4//ng2b97MlVdeCcCf//zn4H5jxozhvffeC/5ummZrn6sQDVRXV9O/f/9IV0PEIjuYVBPZesQoG1taaqKQRkc8N75VQc0FF1zQ4Pf777+fhQsXsnz5cpxOJ8uXL2fdunWMGRMY+/jII4+QlZXF888/z7XXXttkmZ9//jknnHACl112GQADBw7k0ksv5csvv2xYUYdDWmdEh7IsK9JVEDFKWmrCKzCxoZzbaNPlup/qsyyLRYsWUVFRwfTp04NDYuuPIjFNE5fLxbJly5otZ8aMGaxcuTIYxGzfvp0333yT8847r8F+W7ZsITs7m0GDBnHJJZewffv2o9bR4/FQWlra4EcIgKKiIhnxJEKmbd2qxfqCOTXStRkWkigcvSIdbLb6Hbd27VqSkpJwu91cf/31vPLKK4wePZqRI0cyYMAAbr/9dg4fPozX6+WBBx5g//795OfnN1veJZdcwr333suMGTNwOp0MGTKEU089ldtuuy24z7Rp03jmmWd4++23+fvf/87+/fs5/vjjKSoqarGu8+fPJzU1NfiTk5PT2qcrYlBhYSGrVq1i4sSJka6K6CICM6WG/mGttV3zrVUuvOFgI0FNNNJE/hXf6qBmxIgRrF69muXLl3PDDTdwxRVXsGHDBpxOJy+99BKbN28mIyODhIQEli5dysyZM1vMf1m6dCn3338/jzzyCF999RUvv/wyb7zxBvfee29wn5kzZ3LxxRczbtw4zjjjDBYvXgwEcnpacvvtt1NSUhL82b17d2ufrohBGzZsYPr06RH/RiGObk+pP9JVAMBvWTiMVuTx6ZoZjyXvIyxsW2PKuY06rWnNDJdWzyjscrmCicJTpkxhxYoVPPzwwzz22GNMnjyZ1atXU1JSgtfrJTMzk2nTpjFlypRmy5s3bx5z5swJ5tyMGzeOiooKfvjDH3LnnXc2OTIlMTGRcePGHXVkldvtlnV9RCMJCQnNJq6L6NI3JTomPffbfkyzdS01EPkVi2OVBmRew+gU6e+K7X5ZaK0bTTGfmppKZmYmW7ZsITc3lwsvvLDZx1dWVjYKXEzTrFnArumoz+PxsHHjRvr06dPe6otupry8XFbi7kKi5bqltW7V0P/aBTiR1oSwiIYV0EVjkW+naWVLzR133MHMmTPJycmhrKyMRYsWsXTpUpYsWQLACy+8QGZmJv3792ft2rXcdNNNzJo1i7POOitYxuWXX07fvn2ZP38+EBhRtWDBAiZNmsS0adPYunUr8+bN41vf+law2+rWW2/lggsuoH///hQWFnLfffdRWlrKFVdc0VHnQXQDfr+fL774ghNPPDHSVRFdjGXbrcvhqJnGXy684aE1mJFuEhBNinTrZKuCmoKCAubMmUN+fj6pqamMHz+eJUuWcOaZZwKQn5/PLbfcQkFBAX369OHyyy9n3rx5DcrIy8tr8I1n7ty5KKWYO3cue/fuJTMzkwsuuID7778/uM+ePXu49NJLOXjwIJmZmRx33HEsX76cAQMGtOe5i27k8OHD7Ny5k4kTJ+JyuSJdHRFh2rapLC1BGUZgQk/DwDCMwO+GiVIq+DuArW2MVgQodat0h6X63Z6NlkThaKQj/5pvVVDzxBNPtLj9xhtv5MYbb2xxn6VLlzasgMPBXXfdxV133dXsYxYtWhRyHYVoyjfffMOBAweYNGlSpKsiosA7zz3LE8t2EGcFZi5X9aYNU0c2oiuD6sR4puSs5sCb80CpQAtMvRnOwQjcpxUoA1+lB3eqV4Z0h0lgle5I10IcSUdBB1R0ZOEJEWaGYTSaPFJ0XwcOl9HLU8hNP7k8MPzatrHtwG3w//qI3+2JR/we+LFsC639Nb/7sbUfbVuYDhfZw0dF+qnGJK2R5U1EkySoEUJErXB979Na0aNvDkOnHhemI4hwknlqopOOgu4nCXWFEN2OrW3pvujCtNbStReFomCaGmmpEbHv888/lyURuiht21SXlzfecMS3wcYTKTb+ulh/F79lyQwyXZhGyeinKBXpSU0lqBHtt/JpsLwN78saDQNPiEx9jnDgwAG+9a1vBX+vqqpi9+7d+P1+LMuiqKgIp9PZaP4arVs3Nf6QIUPo0aNHh9VbwI7VufzowyXB3zWqcSJvPS1tr7+t2oxjWt/4jq2s6DSy9lN0ioZlEiSoEe1neeHY6xre9+XfoyaoqV3d3ev1snbtWrxeLyNGjMDhcOBwOBg1ahQOR/veClpr3n333QZzMon2G1XxDZOmjmfQxLpZyZscYXFEu3fjZvDGj8kaNKQDaigiITAZYqQvn+JIXXKZBCG6qtzcXCZOnEhCQkKHl33gwAGys7M7vNxuTykyBwxi2LTjI10TEUUkpyZ6RboBTV4VIqZt27aNPn36kJeXR1ZWVlgCGtu22bhxI2PGjOnwskV0fPsT0SWwALq01ESbQPeT5NQI0aHee+89UlJSgMACrKNHjw7r8ghr1qxhwoQJEU+Qi0VKKbQtQY04Qivz3UT3IUGNiDk9evTA6/UyfPhw0tPT+eyzz5g6dWpYjnX48GEA0tLSwlJ+d6eUCq54LUQd6X6KRtEwT40ENSLmTJo0iUOHDlFUVERxcTG9e/cOy5BurTVff/21LJAZVgptS1AjGtJaR3yUjWhK5FtVJdQVMcmyLHw+H/v27WPw4MFhOcaGDRsYNWqUTNceVlHw1U9EH4201ESpSL9b5VUhYpJlWaxatSps3U5VVVWUlZWRlZUVlvJFnUh/SIro09o5pETn0FEwUY0ENaJjRNkIlbi4OI499lhcLldYyl+5ciWTJ08OS9miTuBDUi5eoglKLl/RJhquApJTI9rP4Qa/B5zRsxRBWlpa2JJ38/Ly6NOnT6MZiEU4yDdy0QRto2TyvagU6SHdEuqK9nMmgK8y0rXoFJZlsWvXLoYMkdloO4OOionXRbQJjLKRy1e0iYbRT/KqEO3njAdfVaRr0SlWrVrFxIkTI12N7iMKPiRF9Ank1ES6FuJITS5h0skkqBHt54jrFkHNoUOHcDqdJCcnR7oq3Yt8IxdH0GhpqYlSkY415VUh2q8bdD9prVm7di3jxo2LdFW6GflGLpogCeRRKdD9JDk1oqvrBt1PGzduZOTIkTInTWeTi5c4QmDiPS2JwqJJ8gkt2i/GW2qqqqooLS2lV69eka5KtxO4gMnFS9SpXTZDup+iTzSk9curQrSfwwWWN9K1CJvc3FyZkyZiJFNYNFS7wGmkuzlEY9GQwC1BjegAsfvh8s033zBo0CCZkyZSJKYRR9Bao1ES1IgmyeR7ollWaSlGcnLbPjxsf+smLdAa8tdA8S4o3g3pA2DEeXBkDovWYFtghv+lW1FRweHDhxkxYkTYjyWaVvOdPMK1ENGkrvtJXhfRKNLdxRLUiGYdeOhhnP1zUKYjEJw081pV1cUkDErGPbzenSnZsOIfgf/b/sCsw2Mugvj0xgVUHYYv/wH9pkCvsTD6QjiwGb58PHBcy1dzIBVISDYcMOPnHflUm/Tpp58yceJEDh061Ow+pmmSmpoa9rp0XzKjsDhC7ZIskrQfdaJh7ScJakSzXAMHknH5nKPup4t2cPjpJ3CfVu/O0Rc23MlTDmtfCOTeTJoNrsTA/d8sgZLdcPxPA6OoamUOD/wcqboUNi1u/ZNpgyFDhlBSUtLiPtu2beOcc87plPp0WxLUiHqCo5/kdSGaIEGNaF6o34RC2c+dBFOuCgQlXz4O/adD4UboMQSOvS70OlUdbrq1JwxCWQrh8OHDnVCT7klrSQgVjdUlCktLTbTRUTCvlLwqRPMMhbbto+4W+HAJcXrsuBSYcXNgAcwhp8Ggk1pXp4L1kDWqdY8RXVNtN4PENKKeYE6NzFMTdXTkV0mQlhrRPDM5Bbu0FDMcq10PPrltj3MlgL+6Y+siopIOpgnLxUvUCY5+ktdFVIr0X0WCGtEs5XRgezyYka5IfaY75mcvFgG13QzhaM8uKSzgwK4dKMPAMAxUzU/d/81m7q/9v4lh1v5utrCfgVKGdKF1pGCisJzTaBMNyyRIUBMDChf8GTM1hfiJE0nowEnivDt3knz66Ufdr1NbHAvWweQrO/OIImLCl1Oz4vHfELfvczx2Z30EBuZVUYYK5oJobaO1xrY1tgaUCYYZvFWGia73O8oEZQTvV4aJViYYDpThCOxTc3/gPrPuftMZGMVoOFBmzU+9/2M4MUwTw3QEAjLTxDDNYNCWmJHBsKnTm312nsoKqsrKGjzHwP8DzzUQ3NXcb6jg/2mwrwopAKzLtZLsCdGYBDUxwCotIeuWmyl+6WU827bhHjIEZ79+KKcTZZqYbRxybCQno0KZdE534kgEbYMpE+F1B+Hsn3f4SvEOPodp19yGtm20bWPbNtq2am7r39dwe+P7W3qM1eT9WutA4FBzkTeUxvb70ZYX7fdi+X1oy4e2/GBZaLvm/7a/7ta2arb7QVtoO7Av2gNWBfgstG0F5nXSfrDtercWyrbQ2kJrG6UDz8Fva9B2IOCydU3QZXFY2/Qb9THxSU2vUH/3r+9hXxsaUAPdSE38oWsCFqUUKBUMkAzDwPZ5KHWmyDpsUSgKRnRLUBMLEo+bTsGDfyDzpz8BrfHm5VG1Zg1YFtXr15N1663hrYDWnfdKlm9n3UftN/IwXLy0rXG4XCSlZ3R42bFmy4rP2fXET1ocNFDgczDnuL4MO/b4QCKvDgREgZ/aACkQzNX/PzUBXuB++4j9dU05NrZlY1t+LL+F37JQhkm/UWM68SyIUETDMgkS1MSAlHPOJnHGDIr+8QSZN/6MuFGjiBsVGCHkb2HiuA6jlcwlIjqcDut8wjZaAuTQaI2i5W5AjSIjuy8Dxk/stGoJ0RQJamKEXV6Ga9Cgxhssm8qvVqGcjkB3lMMR+HE6wQz00aNqvg3XfGhpvx/t86OrQx1lFAXj+ETs0eFLFFYalIqqFPioFXIOi3yx6fYC3U+SKCw6gJGUjL9gPxVffknisccG70+ddSHe3bvB78euqED7fIGAxecD26ppAg4081Iz/wM1gU/ijBkhHVvbdueMRCgvBFdS+I8jokNtrByGi6XWduQ7/7uI4GR3Lb3Ho2F+fBF5UbAArQQ1McJMSqTHtddS/MqrVH61ioRjJgXuT0khfky4+547acXcTW/A+EvCfxwRFcLb/aRl9EyIQltAUlprRXSQd3WMSbtoFhXLPgk2GXcKffRZhzuE5QtMvie6hzB2P7VqBfnuLsS/g5xOoaMguJWgJgalfvvbFD32ONrr7ZwDdtboJ/lm3a3UXUvDFdTI6ykUIa/BJVGNIPIvA3lXxyBXv36kff97HHz8750T2HTW6KfOahESUSG0bo+2siWoCVEoicKB7zUS1HR30bD2k7yrY5QjPZ2M2T+g6Mknw34sbdudE51HwztGdJ4wJgpLS03oauenaXkBSenOE9Ex+kne1THMTEvDSG56BlCoWRjOsjrgSPKBJjpeWBe01FpWeQ5RYAHJo7fUCBENZPRTN+Tds5eyd95BOQLzdGRcfnn7Cgx84rW/Yi2x/IE1bET3EUyqCUvhEf9G2WXUTL53tNMl32tENOTfS0tNN2N7vZS89ioZV15B+uzZoa3tdDSd8DXtm11f83LihLAfR0QPHe7RT7J2UEhCX0BSopruTqMj/iqQlppupvj550m/7DKUYXRQ11Pteh/heylXVJXxys5t9Bl2MruqPAyId7e6jC+Ky/HYmpMymu+Oq09rjQ1YWmPZXmxtYWkLv+3Hrlm3xtIWFVZFq+sCgQnNNq8owFftbxATBv6vA7cN7tfB7UrB4EmZpPSIb9Oxu5rwtKhITk2otLZJdVbz0W9n16wKHlj9u5I4thoDMZWi0ojrvEVthWiBBDUxLm74cA4991zgFw0Jxx6LIz29boeO+CDq4MlEtW2zas9mVu3dirZ8OA2DH089naSkdO7blk92nLPZJkalVKM5etaUVXF2zxQSTIMn9xwI+XGmUphK8cqW17i8bw8MZeA0nCilMJSBqUzeO/Qep3Jqq59j0b4KXvvvWxjaWfcnCJ5DVfdvvW21//VQxgnFp3Did0a2+rhdSWgJqm0tXFpqQjVg3CRWbboU5atE6dqVv/3EVezEdg7AZ9ucmBNP9ohRka6qiLDAly5ZJkGEUcLUqSRMndr0xo7qNurgjtR/LX+DIclJXHnMqZjuxAbb5g3p0643zSltWJT58/xsLhx6TpPbvtzwZZvqoW2NoZ1c8fMLyewfWutRrYV3vYTdworJsaL0YCEABdu3MmTytI4tXNtId0loUrN6ccpP5jW6/4v/PMDPv39rBGokolU0LJYhX1W6vaZfgqX79mGH2j1l2x0X1GhNlW1x/LjTGgU0EJlvAeGcnbktZStFt5iV3nQE8r3iEsOx3pcOLOIqhIgp0lLTnR1xQdVas+uzz9jy5ZdYtqb/iOGMPv/8EIrpwKDG78E0OyB5uQOFJZBqZ5HRMB15uMUnpwCQnt2v4wvXMvpJiA6ndcRHP0lQ090pxeHdu1n71lt4q6roO2QIp994I8oweP/hhxkdShnaRnXQcOtOXbMqCrTt6SqI/d6nYOCnwzKTtOTUtFc3e6uKEElOjYgIrTXbd+xgy8YNpFdWMPXii4nv0aPBPiFfSiyrw1pqfChc3aAVIni62vJUFdjd4hzVBB3heKpaVukWIhZJUNMN7d27l+3btzNkyBDOufvuZvdzhTiHjfb7Oma+G8CnwdGdmiHaKvZjmuA3vnC01GgZ0t1uke5mEKIpEtR0I5ZlkZubS3p6OieeeGKHlau9XpSzY15KCU4XFVZ0XbHD0SVWe0FoS25MN8kTrhfUhKHsjswDE0JEDQlqugmv18unn37KlClTSG5hPai20D4fytExLyVlGNhah31Cv9YIaz3amlPTPaIaIIw5NdJSI0TMkXd1N+D1elm2bBnHH398hwc0ANrj6bDuJ4BRSXFsKsjrsPLaK6zJy22JlxTdIkszGEyG47lqZEi3EDFI3tUxzuPxsGzZMk444QTc7tYvLxAK+9A+VHrvDivvuBHH8/mOdR1WXnvY2g5LS03dWo2tL1t1k4aaupaasGQKIx9/QsQeeVfHMI/Hw6effsqMGTPaFtCEeDH3bV2Pa8z01pffDGdCKtrydVh57RGuoKbdpKWmfaJhOWEhRIeTnJoYVV1dzeeff86MGTNwuVxtKyTEi4ldWYmR1uPoO7ZGlFxwbG1jhCX2DzbVtJpCdYuWGhXGlhqFDOkWoqNFw+eSBDUxqKKigi+//JIZM2bg7MBcl2aFY8htN2iJaJducH7CGdQEFrSMjsBZCNFxWvVVZeHChYwfP56UlBRSUlKYPn06b731VnB7QUEBV155JdnZ2SQkJHDOOeewZcuWo5b70EMPMWLECOLj48nJyeHmm2+murq6wT6PPPIIgwYNIi4ujsmTJ/PJJ5+0purdRnFxMbm5uZx44omdEtD4d3+D2aNXh5ZZWnYII0paaiBsc78BbWuQkpyajiCjn4ToaNHwqd2qd3W/fv144IEHyM3NJTc3l9NOO40LL7yQ9evXo7Vm1qxZbN++nddee41Vq1YxYMAAzjjjDCoqKpot87nnnuO2227jrrvuYuPGjTzxxBP85z//4fbbbw/u85///Ief//zn3HnnnaxatYoTTzyRmTNnkpcXPSNkosE333zDli1bOPHEE3F00BDro6l88zkSzv1Bh5b59Mr3uWTyGR1aZnvoaJsMUCmwYz+sUYQxpyYq1hMWQnS0VgU1F1xwAeeeey7Dhw9n+PDh3H///SQlJbF8+XK2bNnC8uXLWbhwIVOnTmXEiBE88sgjlJeX8/zzzzdb5ueff84JJ5zAZZddxsCBAznrrLO49NJLyc3NDe6zYMECrrnmGq699lpGjRrFQw89RE5ODgsXLmz7M48hhw8f5pNPPiEhIYGpU6didOJQVX9hAc6BIzqsvE/Xf8LU7EEkxDVeoTsSDIzwXPqCLTVtK72zQxqtNQ8++CCDBw8mPj6eCRMm8OKLL4b3oEYYc2pkmQQhYlKb39WWZbFo0SIqKiqYPn06Ho8HgLi4uOA+pmnicrlYtmxZs+XMmDGDlStX8uWXXwKwfft23nzzTc477zwgMMfKypUrOeussxo87qyzzuKzzz5rsY4ej4fS0tIGP7FCa82+ffv49NNPee655zjhhBPIycnp3ErYFh09gG79oYMcN3xKh5YZbvu2HOY/Dy1l0Z8/YP2nu0N6jF3T0qLamtfRyVHN3Llzeeqpp1i4cCHr16/n5ptvZvbs2Xz00UdhO2a4Wmq01jh0FY56n1VCiNjQ6ivS2rVrSUpKwu12c/311/PKK68wevRoRo4cyYABA7j99ts5fPgwXq+XBx54gP3795Ofn99seZdccgn33ntvMKl1yJAhnHrqqdx2220AHDx4EMuy6NWrYd5Gr1692L9/f4t1nT9/PqmpqcGfTr/ot5HX6+Xw4cMcOHCA/Px89uzZw86dO9m0aRMrVqxg+fLlfPHFF3i9XqZPn05WVlants4E65n7Ds4REzusPH9VMYYjPHPptJVS6qjX1B3rCtm9bycHDxzi6y82h1SutjWg25TWoVTHjX4KpQWmoqKCBQsW8OSTT3L22WczePBgrrzySmbPns1jjz3W6vJCpcLUUmP5/TiwcMXFd2i5QojIa3XixYgRI1i9ejXFxcW89NJLXHHFFXz00UeMHj2al156iWuuuYaMjAxM0+SMM85g5syZLZa3dOlS7r//fh555BGmTZvG1q1buemmm+jTpw/z5s0L7ndkM30o0+jffvvt3HLLLcHfS0tLozaw0VqzYcMGSkpKiIuLIykpCYfDgcPhwDRN4uPjSUtLY9iwYZimGenqAlD50Vsk/+je0Pf3VVLqLUVrTZ+kPo22f7D+U04YMrEDaxh+Pq9FZbmHeGcyvftkUVlRTcmBSkChVN2FWSmFMupex9UVPkBhtKmlxsbvK6OyckfNcQzACNwqA0Xtbe02s+a4BoYR3yAAnjt3Li+//DILFy5k2LBhfPzxx8yePZvMzExOPvlkADZs2EB1dTVnnnlmg1p4vV4mTZoU/F1rzZ133skrr7zCI3/9G0OHDOXjTwLlxadlcPIpJwf3e/hPf+SJxx9nf34+w4YP58475/Ld734HRf33es25Kinn4MadKJ8NpoEyDJQBGoVl+9GWH8vnx/JbgdW3USil8CiLpD4ZOF2uQGCkFJbfT+nhw3htA7X3S9gVH2gJ0jYQuF2xo4h13l4MGzqywfNVKlD3f//9/3j1+acpOlBA/0FDuPInt3DazAsDf29gTN9UktwysFSISGj1O8/lcjF06FAApkyZwooVK3j44Yd57LHHmDx5MqtXr6akpASv10tmZibTpk1jypTmuxPmzZvHnDlzuPbaawEYN24cFRUV/PCHP+TOO++kZ8+emKbZqFWmsLCwUevNkdxud9hm0e1I5eXl5ObmMnbsWMaMGRPp6oTMrvJgpqSGtO/r215n0+Kf4lUKr1JcfflSBqQMCG4vq65ia0UlZ2X1DVd12+Tv23IZnJjU5LaSA1XsWltEXNFq0pOzcLvj2LZjK3+f/3LdTvUbGY5YiVJh4HC1PkD1Vu5mR+HXvPTy56E/SCssXzwH180CFO4EJz6flz8s+CM3X/Fbdn1Rze4V61CqJ5OGjePWG67nhu9/G9Mw2LEv0NJ65blnkRTnRteszaW1xmEq5l9/FTmJI0gxevGnh/7I7y+7E+OzYrZ/toJ+xDP0mBO45jd3MebHNwOw7YXnOJD7BcN+cBV9eveheNMGLpv9A36/ZhPpo8YwusTign2ByReH9pxBr88yqP4stG49CJxiDRja4t+77sKvG0/k+NPhu3FvfgA2P9Bo21RgqJ3E35Z9Cw91czxpFEuXfsqmb7Zx5pknk5Gexu7de7jr5z/km+WLGTCgH73UYT6afAO/uqjjJqMUQoSu3V8ntNbBfJpaqamBC92WLVvIzc3l3nub/zZfWVnZqOvENM3gh6bL5WLy5Mm8++67XHTRRcF93n33XS688ML2Vj+iqqur2bBhA36/nxNPPDFqWmBCoT2VYIb+8smvyEc54hh46m/Y+d6dVPgajoh7Jvc9rpx0ckdXs93Wlh7mb5PPaXKbt9qP05vKeRefQf/RGThcJpP2DA1cVLUOfPEP3ja8T2twxztIzmh9XocbF0mmwfnn3wPaDozO0nbNwo+1txqtbTSB1guNTemhUt75MouU3hZDJw5k3Ter8fm9/OVf9zQo3+fzkJ2eSkpKCrZl0b9Pb5wOB0np6Xz73Jkow8AwaltMDD548lHS4geTMq4PXr+PuS882KC8Sp8X59CR/OzMU6muqOCK637Ab198leFTjsXWGkvDo+XFeDasZsdpF2Ck2jwwNRuN5mDeLjzajys9AVwKbQVOprY1SisMw8QwTQyHieFw1DTuaA6s20fqFgcjzr0YZ4IzOHReKYOE5GTcn9ZMCfHTXEAFmmGUAhTfrMtl0Ps/4nrHG5T8cCWu+EBQW1lRwR8X9GfRq28yeeq0YLfkr276MSVVlVx98+94+qm/EedpfrSnECK8WhXU3HHHHcycOZOcnBzKyspYtGgRS5cuZcmSJQC88MILZGZm0r9/f9auXctNN93ErFmzGiT5Xn755fTt25f58+cDgRFVCxYsYNKkScHup3nz5vGtb30reJG/5ZZbmDNnDlOmTGH69Ok8/vjj5OXlcf3113fUeegUHo+HrVu3UlZWBgRakkaMGEFiYnSM9GmN6k9eJ27KjJD311pjKpOJmRPZScM1jz7Zvp5JiQ4SU7I6vqLt1FI+R+2FskffJJLSA8FJ3xHpYa+TYbhIShxBetrUVj0uOb4Y+IpRJ1pMOX0YxheHAFjy9lv07VvXQvbUL26lz6BxfOfmXwfv2+6FRx99lFHHn8SMGTMoLS3ls88+IykpifTEPqh4B+5Rgee++K03G5T34w83kOyKY1avdFas2Iq3upr7vn9xg7rVdmWdUK0oNU0Sjw2sJZZ0bONuylAUH66CLWXMOPdbJPVMabzDp7Cv95lk9xzWaNOIkwaxfPOnHLfnKba//zDHXn4/ACu2rcdTXc3siy8I7mtrm2qPh7j+8Xzr9ZM4Nb4C218ORM+UBEJ0J60KagoKCpgzZw75+fmkpqYyfvx4lixZEuxrz8/P55ZbbqGgoIA+ffpw+eWXN8iLAcjLy2vUp6+UYu7cuezdu5fMzEwuuOAC7r///uA+3//+9ykqKuKee+4hPz+fsWPH8uabbzJgwAC6ko8//phjjz022JLVlVWvWEbazb8/6n77yvexp2wPXxV+xbTqUjYc2gCAUZMhW+71sjZvPT8++bthrW+btZC3FdYZb1sQmHyvDcesOee18+6MHj0at9tNXl5eMH8GICPOT2pcw6U17r33XrKyspg/fz7bt28nLS2NY445htt+9Wu+8VRjOMxmy4v/ppyUmmPbduDYixcvbhD4ADhNJydtO8QPaP+opNrz09yfr1IlUB3ffPf1tKsXsOLPeQzb/jSlB35CSmZ2o7q/tvkdHlv3EIaVzpiMU8hI70WC5xkSepS1u/5CiLZpVVDzxBNPtLj9xhtv5MYbb2xxn6VLlzasgMPBXXfdxV133dXi43784x/z4x//OKR6RqvaUVixQFsWKi7hqPv9/bXZxBdtI0cpCkwHpq+ywfanV37AleOOi5q1ntokEvPgteGYtUnJ5QcV+7Ycps/QNG699VZuvvlmbNsOtsB8umUnrp17mJk3h4x+ORhGING4qff3O7f8gXL/YYZOOY7k5OQmy9v+xn85FJ8I545vNvAB+HB9Ph5TcXp2RsOnqjV/+MMfePTRR8nPz2f48OHMmzeP73znO80+1/379zOEJHw+fwtnpIVWOMNg0Oy/4HxkCpv/9wDHXPOXRnUvz1+Mu5ebGRkXM2gjPPr7/2P3nl1k5uxj9O9PaLF+QojwkBT9Lk5rjfYHcgzKV+/HX+oh7aQBbZ//pIMlVZexf+Q5zJn0E1LdqRyuPsweAi01y3ZvY5KjisQe/Rs9zrItblo2n+XFgW+99bur6o96U6jgxLDxysdTM37MoNRBHfcEWmqFidQpVm2buqV2srkNH7rZ8OEqxpyYzemjZlN+gWrQApNhwmmjhvD0L39KYnoGI48/kVEzTiVr0JAG537TZx+zdu9HjEs/ifSiDLTWTbbokDOMnO8HBgI0F/h89tlnvLOrFGbO5OShmQ3qHcoIrSPVLhFS2yp8ZGA0NNXP9Rdv4ydXNH5s/X337jnI8IyFzNnt5jvfv4Rf/OIXwbrPnnE+//vwff71hwdIPhTHU089xUdr57LjYNZR6yeECA8Jarq4HQ8u5XD5Prb/5TN2HNhNhfJw3rjv4ejR/jk4mrtutqa7pTQ+lT4bl/BKWSF3XfwKh6sPA6A0rNm2kp+cdHGTj1vw+PW8lZXFNf1643bEBbsTao9d/3eNptpfxbP7ithZsrNDgpqtJbs57cuNTEvyNrtPIKDSXWZtScNhYsYVY1WnEZ/iYv0n+wAY5j6VH/7jBkbPyAbgyV++x8BxboZNTmXLl5+zcdlHrFz8Gul9+jJqximMnHEyls/H2wsfZtSMU5hx6pUc+tdGqjceIn50j0YtOucvXk2vehPyNNeVxWnf59gKcJh1+9bOkfPBBx8wfXpgRNHgwYNZtmwZjz32WLNBQ0ZGBlCBoyYv78jA6N1bjuHGx99n7Pc+alRG/X0T412sXnAxt973R6btfISLvvdXevX6TbDursR4KkpKue63d3L22Wezbv99ZE2dQOLBPi3WTwgRHhLUdHG7Dq5jkKsXWwt38fLyxby66h1K/3g9w0ccvYm+rayCAhzpTQ9zPtKNF/2Hv3x0B0mFm4BAK0t/n5/7Fz/A7CnXgtF4xFfu//7BY5k9ufiDt7nj/3IbbW9KUVUR/9p7X+hP4iiGpuaw4dQsrl/5Ll8c2Mm0zIGNd1KAbmOzSTuoNh7SNA2Gnn8bI4Y/QL+ci1ixeCfeSj8lB6v47OWtjDqhT818OnEkZfQlZ8wgcsaM55TLryVv3Ro2LlvKitdf5rMXngMgITWNM3/0MxymExwGh17YTJ9fTcWIb/ixcuQqS811Zf3o3fXsqG44kjLUOXJa0lRg9INJiXxwqHHg0dS+xx2bx+ezL+WxlUv4+cX+BnVftOQNLp15AX+b/yce//1D+PxVYHyB9hNy/YQQHUeCmk6itebZZ5/lkksuCTkvoFbJgULm/+5+/v3CSxQePMiQgQO5+557+O73vodHVWEA75Xm8lFeLr8494ccP+U4tqYXtbsJvPZC5LN9rC5cjc/2kRGXQc7XG3GPGIut7eBEZ0c+V0tbPPH57yjd/iHxlQfQCT0BGN1jNPOHnUCuN4VHhx/T6JgVRQX8rHAZ/auL+O3di0Oua11iaMf1CSU53Dw99VyuyV2CVnBcz4ENttceqvNbanQb83gUyrAwnTZKKY49P9Citeb93ezZdKhe4nPDFCfDNBk44RgGTjiGM66tZtvKL/nms0/oN2oMTldgHqjM68ZxYOEaSj/MI+3cwUfWNqS/y6iEON5WXrweC5c7EOy2lFjc0hxU9Y/XZGDkrcRr72fS5IYjo5oLojweD8f0sknOPHLyzkDOznUPzuPn53yPJ176HkbOdK469uYuMUeWELFGgppOMnfuXN544w0effTRkPMCas3+9iy+WLeB844/lp6pKezIL2TOnDlk9eqFMgyqvdX89YmFfPDBB5hflJLVoycz5lzQbBN9qImXtdfN93a9x4r7fkFposJvwC39ZtLvB1dz0xOTWLl4D3tXJ1G4vzBYzo7MXArW/ZcUM46D6f0Z2O8cRvevq8MWj0lPlwO32fBDX2vNnfdfwqHjRvN8wmTie/ZqsK21yaIdwTQMnphyDleteBOnMpnco+6iVnfh7OSopo2jn4ILOB7xUE+lD7/XxrJsTNMIzMrbTBDidMcx8viTGHn8ScH7tGVz6L/fAGDEO/EXVTXo/jxkQkoI9T0mI5Hq/WVs2lfC+EGBZOGWEotD1VRgVP6XGRT3OYkhs/901H0BVj3zS44re4+siQ3r4E13oxwKV4XF0KFD6dkrDrN/j+AEpUKIziVBTQfw2Dbn5G5mR5WHaluT6XIEpnuv2W5XVbH+j3/i2zf8hIWHq9Fffg3uNHpNn8Flt89j4k9vDs6C6i4tZurXn2LYFkoZeL1elnz+JfOuuZyb7v0d5YcO8fRfFrBr/35uuvYafnTOd7DLPcFvl7bPCuSdXAt+v5/BvQfy6G3P4zVVMNn2jaX/Yc03X3LxmVeQ1aMPW3dv4tJLLuOz2RsZPiAwo/HKlA8ZtL+UD+9+kSp/NSpecdVd/+W/t3+PXV+8zKtpS9m9aDs71lZz2necDM4eyI7Nh7j00u/xsx/15LJ+sN3poWDiyfzsuNuD52rZ+8+QWHYB31qdy18/uh1D15wnBVg2X46fwfQ1L3PM/X9rcI5DSRa1jWR+uuwjkj1ubDS2JjC5Gx6qE98jKZ7gBGun90jj98ffGtLf1zQMnpw6kytXvMUvDYMJ6Q1bDDqipaY1QZs6Ymbi0NXmqtgN7h00MZMVi3ey/uN9ON0mVWU+DDP0Fi+72sIuC+Qelb69k9K3d+Lqn0zCxCziRmew0w07jzjmkb7aWcT92/dDAhRW1nVBtZRYnJSUxBVXNJHpe4SmAqN9fbLpbeygd79+R90XoNp9EMx+uFwNh5vv8xym58ye/PPBh5jQuz8HC6rw2wX8bc3fQq6fELEiGtILJajpAAM++rrB70Pi3ZyUkUzNBLLkrVnFOq+H1//+KPz90eB+ls9Hv9FjOW/GCSjAULBy+WfEFe1nwkXfp2dGD9Zv3oL/yX/x4L/+w4PP/RcAbdt4fT5GDB7M0NReVJcEhlYvXryYTFLw7C4HrfGV+9BrD1PiziZlchZaQ2VVBbf+8U3+8tt/MmbYRLSGU+zTOFSWz5otn/Otcy5CK8XfK+5nY4rJxUPOJ10pevUcyJgeYxj2k1+ysiwfn8/Dm8vW8JO/Xc/gcf3BcNBrpoMdpYv4eGsV/m9NZVjqYM4bUTf/zKG8LSTc/mfuSo5n0PmXBp6LrpvWHq1Zlvc08b2zG5zPUJJFe8T1IKHsTUzfBE7omYRpKEwUpgH5lTv5vOpdJqaezqjMfny6fw2fHW7d39hhmDw1dSZXfPkmvxnlYGRqr7qotQPeya0e4dOm0U813UtHPNhbGehCObCrlG++2M+QSZkMr5n8LhRmopNeN0/m4D/XkzAhE0dGHJWrD1D8xnb43zbcZyThMRWD3lvFuZaTBaeOxO0KfPRYts3Dy7bxJ185AxVc43MzdUDDId3NJRbfcccdIdWvqcBoY/KZ7HrzL/jyzufnf1vc4r6lpaW8unw3g80CRv7rN2Qecz6DRh+LMgzKPF6yvp3FVadexfz589m6dTPxyZs5YdqJIddPCNFxJKjpAEMT3Gyt9PDxsSPZW+3lhPQkXPUmGPyiMIO/Au+8+WaTeQE5OXUz6f53czK7gZFnnEu/nj3wpH4BwOJmHuv5Yif+isq6b5dz5gS3l+WXU7JrFamjejDyW4Hm8BUrVuD1evjFfdc2KKs28fKUS8YCoJ9UnJ85m5tPa5jMOXvClcFyfJ7f8vebnmqynL+c1XD1Zr/Xw1fXzyZBaUb88yn6DRjb5Lk0//RCYEHGekJJFlVK4fClMygxgz9eOK7Bfu9s9fLFp9Wc3fcCvjvuBMq+WMB7Bw81efyWOA2TJ6eew5UrlvDbUVPprQL5GO2NaVo/wqdNU+/VUDWLN9bZseYgAFtXHWDAuJ6cdd3YVi+06UiPo/fNk4O/J0zMwqrw4d1VyjMfbOfrVJPDmXE87vSw7Z21/H3yUJxxJjd8voXlcTZX+1z85vThuN3OxjVuJrG4NZoKjEb0TOPeXh9x4IsXyJz23Rb3HdzDyYPHGUzb/lfY/lfWnvIE4075DpZtoZTipptu4hc3/4IFT07DMfJ8bjx+Xgu1ESI2RcNEIhLUdICzeqRyyFdET5eDoQlujCPyEdqTF3C0x25dvoMkdwI3/fRnjb5dvvu/93GuPcTxfes+sENPvGz5stnaBM535l1N/x2lVDx0W7MBTe1RjSPuC/VYlnGYFGcTSy0c0T8U6L1pW1gQZzr555SZXJn7FndkT2yy/NZq7QifUHOhm+rSmjWrghEjGtY3JTMe02HQb0Q6Z149uo0rhzdmJjqJH92DUUt3My4ugYxzhnPm1gP8aNseTlm3FYA4E57p0YszJ2QfpbS2qZ9AfmRg5Pd62P+nGSQt+RnlfceQ1G90s/tWVVaQt/4ztroSGPrKuXjzNwLgtb1orTBVzSg+feRYLyG6EaXQLeTkdQYJajqA21Ac8lmMXraOK/v25IHhDfvp25MXcLTHnpAQGMFy953z6Ns/p8G3ywljJ/CjPt+iZ05ysLxQA6zAR3PzL8zWBGqfPfsHBr32FTt/cCIzz245x8Cm8Rsi5GMpPw7V1Df9wG0w9ggm8bRNnMPBP6acxRWfLSHdtNqdU9OmET4hHLOpLq0f/vBqxo7dwHfrrUox/tR+jD+1X/MFdYSa0z19aCbv9Urmydxd2DZcPTmH3hlHn5k6HBwuN6lXv4j30ZPwPf0d3Dcvx5nQxDpRQHxCIiOmBoLOra/2J3nTf1h335sUDJiEstIbTgipjgzLhegeFGBraEVKXoeToKYD3NA/i0kpCVy3fieFHl+T+7QnL6DFx+6vCT+a+HZZebCKQ3/MxVfvm3fIAZZq+aoZajnbl79D4u+fZMuU3px/56MtllnryGAq9KBQB9eUaqjmudRceAxUu7uMkhxu7h40ldl7V7a7/6nVLXkhzFPTXJfWf1/4Oc8990GDoCbsjqhrVnIct506ohMr0LzkXgMovOgJ0l/+Pvl/v4Scn72BMloOSoom3MCEVb8hzr+b4tI44uPrtQ5qO7jGlhDdTWAOrci2VkpQ0wFSHCZn9UzlhLTmJ6QLNS+gqdl6W3rslv9+VLtTyPUNJcDSaAzVeGK81pTj93rY/atf4unl5tSFLzZYyLQ5NrrJFqLQgsKmg5rgKdUd+0YbmJjByMIZ7cpwgda35IXyLJqfb6WCsWML2lXf1gp1npqO1FIr45Gyxp/BrrzbGZB7LztfuJOB35/f4v7TZv2Y0hMvRv1lNC6jhASz/rw8ulXvRSFiiaEUdoSHQElQE6VCvgjUvICOzONpWFjjso8WYGllH/XCcLRy1ry3iKxCL95Hfktyco8Wy6o7bqAlpbXH0lqDaqalRtXbh8AFr6MmzIv3JXbI6KdWteSFMKS7uS6t5V/MZNjQG9pf4dbQOpJf3EIy4Pxb2bFnJf03Pkrh6lPImnh2i/un9OjFu/2uZ3L1c/yHL5n21MUsv/JFlG46KBeiO2hPvmJHkXbSDhTKn1JrzXtFpdy1ZS8Ldu5nfzPdVZGmm+3KCd3BLWsBGHtK0+s7NXfctlwU7JoRPWYLLTW1z6ej1vqsGyLdMWXdeOONbNq0Ca/XS2FhIUuWLOGkk05qcv+jHbN+l9bQoUODP337uumTnd4BNY5uR+ZRaa158MEHGTx4MPHx8UyYMIEXX3yxwWP6X/NPyox0Kpc+FNIxxp19DbccKmZMWRKVxmbe3fYVoCGEFkkhYpGhOu4LY5vrENnDx56WGky8ts1PNuYx++vtLDlYwsK8Qk76ciMfFpW2+jieygp2rMpl19pVAFR8WYA3v6JVi022RCuNamd3jc9bhWWA2cT6TsHjHHGxeeeP69myKr/Vx7JrJndruosrsK2jewWCF85Obm8NZe2n+l1aTz/9NNu2bWPVqlW8+uphXnzh05CPVV29j0OHPmtXfX17yqn4cn+7ymir2vfD3Llzeeqpp1i4cCHr16/n5ptvZvbs2Xz00UfBfU2nm9KMccSX54VW9oolJGjNNdtOxrTieGH9ezWTbkpLjeimOn8pvEak+6mDLT5QwqyvtmAoFZxQz0BhKPjwUBmmgkdHD2BWr3RKfH5+sjGPK3I3cNOTDRdj3Pzh2xzq0QPTdOCKTyApPQOf10PeujXsXPMVBdu2orVNRnwfBvQeCR/speK9vZgZcbgHpaJcBv7SwCyv+VuKsVYW4nAZuBOcxCc7SekZHxy6W1Hs4fD+ChLT3KT3TsTnCUzGVlpY3a5z4Sg4zKG0lvNyjhyh8707T+OtZ1bz0eWNV09uSe3Fq6mWGjvY7UTNreKQ5eCqD+9Foxi8Mp9xB+NJdCSCDVrbaG0HYiFPGc64Q6RPSg0MV6S2dUZR7XVSGv8d7IM7gZ4h17VDhPDJ0VSX1sCBVcw4IbSuQIBN38yjqGgpOTlXM3TIrzGMtn9k7P75P+uSaGtHoKm6ubeDXa4KlFNhxLvANGratO0Gu9sVPuwquy6gDI5sC+zg1A5w9eaTj39ItVHFH/+4mPt/dyJ+63E2boLMTDjp5N785jez+eWvpuF0pjNo4PdIqj6EZYa2wr1dtJP7lpk8tPpZDpfu55te67j4nB5MnyhBjeieoqH7SYKaDnRFdk96uhxoDZYO/GltAtefA14fIxPjuG9YX2akB4ZYpzod/HPsIBY4Gr8Ivnrx301euOKSkhkwfhLjTjuLnDHjSesVWFlZ+20820uo2lCEd08Z+G20hhINW7aWsGpzSYNyHG6T9F4JeKv8lByoCt4/cFwPxpzWB4Cs/k0Pbw2Vc99BDvVoflG/pkbo9D+2J95duplJ55pnaQug6UThmtvai+ZpfaezqngxZX4/Ck1m7l4qlBvnoBGBYNR0BPZVCt/ebXhKS+kxLXBOVE03l0LjMmwmrfZwoGo1g0+dEnJd2y3EZRKaykP66OOJDBw4LKTDVFfnU1T0MT16nMKePU/j9RQyduzDra6u/8AnoLJwpGdQO390XfJ2cD7pYICitebRzxfzr7XvUFhRzOD0Pvzs2O9z3vAZgYkZlYG2PSjlrWtrrr2tnViwtBifZw/m5N3k7fbh9drMm7usYb38NoOHJGGah9B6M3vy3ufEysPk5YTWXfrAyx/x3poS7vzJbaw4fJBPy//Lon/uoueUHTC11adJiC5PEoVjzDmZqZyTmdqqxzgMxa9GD4H/vNFom7ZtLMvCU1FO+eFDmKZJRr8cjCa6c5TDIG54OnHDG+ZL9LI1w7wW2tb4PDaeKh+VJV4O7i6nuLASh8ug9+BUMvsnU7C9hNy3dvHM39+BCbC46BVu4MpWPZ/6zL2F6NHNT6rW1Aidal8V2tLEW9tadaxgTk0TLQnBBOGagGda9rH8N/vY4PaP7hlP2ZQRnP+7exo99uCvf8Cht7cz/NtvNtp2eOMGMt7fj9cO7Zt9R1G0vYlXa83OnQvJ7HkmCQkDmt3P6z3E+g2/wDQTGDvmIfbte4ubbvo9K1b0oqiotFULitpFK0iYPJne86496r4Ad955J68U5fL3/z4TnF/n+uuvZ/Svzg050N390h8ov/NJTvrjYtJ2HgCOY8mS95uZ0TsHy/Kx4rNfYTueYtC+xbD8UZh6LZhNf0RWVFTwj6Vr+OAHcUxgIbN79uP9ydfyh42/54PnPoEfhVRNIWJK3ZDuyJGgJoopw8BhGDjS0klMa1typzIUrrjAn9mdAEnpbnpkQ86ojEb7pmUlMOzY3nz1ZTovfAO7fNu57p3r+PHEHzMpq/HMti3ZtW45mYUejEuPbXafpkbo/OipCxnmzObOa55s1fH8dqDLzGxiGHqw+6ktvQJKNdsqYnsD3XtDTxzZhoLboR29G/37X8Pevc+z/Iuzyel3OQMH/pQtW+7jYNFSMnuezsiR91Ne/g1fr70ey6pkwoR/4HAk8+tfP8GyZXmce+5MfvnLX5GbmxvyKvPYdsgnv/VLRjR3zJq/uWEcdR6gQ4c+Zdv2BVT4VvPV9OEcVzEDltwGq5+DM++B7EngTACHKxBN2n5yX3yMao+HM58F2AnsRKsv8Pothg7xh1ZHIWKMtNSIqGMYiinHjWDNtDW8n/c+C9cs5PK3Lmd6n+lcN/46pvSaEtJw83XP/R+9XYrJs29qdp+mLjYJWW56OpLJyclpVb1rW2ocLYw8aVMCZ/MxDYYROObLT1fyk+mtL7rNlG7znDuDB93IgP7XkZf3BLvyHiNv9xMAxMcPYF/+f9mX/19AkZQ0imMm/Zv4+L6Ul5fz4osf8NOfXkrv3mPYuHEjV155ZciBhrYtlBnamITWLhlxVEq1OA9QXJzBoMEPk5IygczMc+iRcSKq7yUw6Qew+Bfw7Kwmi43bEwhc/vnT79K3bza2EUfKlJlseu7fxB07u/X1FCIGqBC7xsNJghrRJEMZnDngTE7vfzrv573PI6sf4eq3r2ZgykDOH3w+E7MmMjh1MPGOeNwONw7lCAY7tm2T9MnXFEwZwOSk5luYmlw9uaSUlVuWc2jjtznl1GMwDAOFgTINlFIoZWCYZr37DJRhUKk9gXpjNlrzqPeAflhneDCOVU2uh3Sxp4RjmokRVAstNfGZmUBxO85y2yhqx3O1jWnGM2jQT+nV63w+X346bndvph/3Lpu33E9x8Rf06zub3r0vwjTjAPjgg9fw+/089th/AQO/38+VV16Jz+cLBhpNnddg95StQ55lt01LRjSl4ZoYwaTp++77DTt37iE52cXYsQO54cenobWP/jlXk5VVb26avpPhug9hTy6U7gVfFViewPNQBjueLsHlvIWqSRcwvd4isuVvvYUjq2G9hehObOl+EtGsfnCzYv8KXtn6Ck+se4Iqf1WD/Uxl0iOuB1kJWWQfgmsP+ij7+QVHLf/IETp2nE38gHiWXLCaT8q3tKquSmuy9h1qNKLqoeef4P/uns+6Y1ey/F8vN1oP6UdXX83d4wdxftMnoNmgxohLBGDcoN2tqme7tSeppp6EhIGcOOPLQGCoTEYM/02T+23eHFgp/rXXXmHgwKE8/fTT9OrVixNOOAGXW1NdvY/f/vbPvPrqGw3Oa233VD/bDnnulvYs/tpQw6AGNBdeGMeYsQ5gIA5HGgC2/QG2beB2ZzYuQinImcqRWb9aa8qf/YTZ376uUevPSyu/IrH6Zaaef2s76i5E12So9i9B014S1IiQGMpgWp9pTOszDcu22Fm6k7zSPDyWB4/locpfxcGqgxyoOkDfVeuxDcWEs39w1HKPHKFj2zZ+TxW2baEtP7a20X5/4HfbRltW3TZbo20/2rbwFh6g4Mc/I++Hydx6RE7GKbPO5V/vLOTNf/+X3I8+bZSv8eKvb2HJ19u5vZn6NRc/VO7bC8CQ44e2/oS2Q0cOGHa5jj6827YNHA6T/fsPcuaZM5kwYQLr16/n9ddf5bjp/2HnTi8LFuzin09fycmnTCDO3btBHsw92g65+6k9i782UPtHq2kh2r37Ge6//3beegsOHqxk+PCkJhOdv35vCV+99T9GzTiFKRd8mz/+6Y/89aGHOHi4mBEjRjBv3jzOOf18PJV+7rztN0w4fniDIfODk5K4+vRrQqujEDFGEoVFl2QaJkPShjAkbUiT2w9tf45Cxxbcya0bCQaByfNc8Ymtflx1Yj7lHti9b0+jnAzLtvF4q8kbtKPp9ZAqKxlsNN01dfPwdI7TTXev3Hz5D4ApKEcnv42UQnfwOlbNKS3dT2VlCt/73pnBQGPkyJEUFxeTl7eLD94/zKBBY/B6d3L11U9z9VX/xDCcKOXA663pnkpOoTWhWHsWfz1S7eKUv7vnSd55t4qHf/IYY06bxOcbGic6+71e3v37/wHw6X//xR//7298tXUn5w4fQGbyGJImTmP27Nn89d6ngUzSshIbDZn//PZf4xw7rdX1FCIWSKKwiElGfDza60X7/Z12wbeDCzw1zslYsjmXv6z7DZcm3cA9P7mlUb7Gl987D8/kYY26rT7++GOuv/YaHu/Xl2eb2vajH3H92Q9gGDM65TnWqZvbJdxWrFgMGCxY8DD/+c+SRoHGqaf1p7KyEoDFb7yBUp+zL/8FtPbTu9e3GDTocvR1t7Rq6YBQF39tia7JzUFBWVkZTz37KQ/dO4ZplUPRrxXz/UvPZ9ns2Q0SnR0uFyPOOo9nCku5atRQfv2d73H9yccxccxo/F4PWcluZs+ezQuv/4sLR9+MYTYO1DSySLfovmTyPRGTjMRAS4tdWYmZ0r4J/EJVm5w2sG9Oo5yMXtX7cB9wM2HssU3ma+THuymIczU5lPj9v/yOf2/N56Mmtr336issW/8GyjixU55jrUDycue01HzySSBfKDNzaKNAw7J8vP3OCVRWpOF2u9m79yBz5tyDz/cL8nY/ye7d/yRv99sYV1dTnfsGWfy8Q+tW/c03VH7xJThMlGGiHCaYDpRp4H0/sHyIUgb/e+IqvF6bX9y1iV+aZwYmpvwD+LSfCaPH8eCDDwZb4Bz9BmD+4BrYvg+/ZfP3T1Zgfr4Ky+8PzGSsYdyYCWit+eOCP/LvF/7ZIDE6O9IJBUJEUChLuISbBDWiw/kPFYFpopzOTjtmbZNnYlx8o5yMHRs2U/ReEZ/v/6DJfI2X84vYn+tveihxdRUDTAfVXm/jbR4P2RlDg10cnUaB5QdPdRXuuPBO/JeVpSgs1CxceBs/+cmDDbZ99dXfcbuLGDb0Pm69deoR5/UUvl7jx+dbz8RJn1CVfKDD67b/vvupWrEi0ApkNx4PZrs0yuWihK8BeON/b9J/0EC0ZVPy1g6qNh7iydwXePLxJ1i4cCEP+Zx89skySn83l6+u+iEAb7/7Ln379mVr7hd89Mw/uPjOe0hK6cNNV9zFtuIVjRKj//jtizi+oxcZE6KLaCkHsbNIUCM6lNaagnvuBQLdUJ2l9pJmKN0oJyM+KRG7r5/eM/txy6VXNsrXGOStYvLg3kDjocQlt53O8s/9/HTfvkbbClet5oPX/B2+UObRuOLgQGEm//j5p7iSSkjMqCS5p0F670R69u1FrwEDSc3o1czinq3z4x/fxeOP382+ffFUV5cSFxdoebMsHwcOPoXWwxg27CzuvffMZvNg7KLPiBszut11OZL2+Yg/dioDn3km8LttgxVIKN+w9heUvfo2tmkxqH8iLqeDvfvzOe3MMwIPHjGckl0HWTT0Kl782aOcffbZrN6ez6rEDJJXLado3dcNWvUG9M9h/SvP89Fffk+fsdP54OsXuOW6uQztP4rP3s3FJImzTp/JK199xfTLpblGdE8KGdItYoxSKvjNuWrNGuInTOiU4wZTKJRqlJOx6Oul3L/qZ0w4dkqT+RobR46iJL+KJ5vomjrcfzD6671NdlsVflpAepIHr6dz38TnXn0pOzd9zYE9BRzeX0XpASjY6iJvVSLoKmAjhvMr4tNKSe7hI7WXm4w+6fTKySErZxBOV1yrjpee7mTfPh8PPvggo0bHM/OcH7Fl6xu43Yfon3M/0HIezNJXwtXP3rBMZRhgGIHsqv2pYMLnH5yFK7WMq757QoOWpL37D3LtgoVU+z3MeuTHuB//KTZQbdng9xE/aGijVr30idP4YsUKli5+Db/l489P3Mefn7iP2mkd/ZafoX1S2HtoG5MZGIbnK0R0kyHdIiaNXLOanbNns/fWXzLolVcwk1o/mqm1rJrbptombEJYJqFvOrde1Lhr6r3tNv6ycn7xi1802vb+qlfZ/I3Bdxzf7ein0yJXXALDJx7H8IkN7/d5qyjYs4MDu/dQtK+c4gIfZUUOCrclYfscQD6oPbiTi0lIryYlU5HRJ5mefXvRu/9gUjKymjzehRf+nFGjl7FpYy4bNlSxc8eDjB23E233ZNiws45eYU14Oto1zc5u3cfxPXThZlLUKJStePDByxg97e1gS5IzIRmrT2Bdsp4P/IW4Xn3w2jb94lz0PLCXPEcc915zaZOtT0PGjoUvVvDow4+wb3cJx598LH0H9mL3tnz2vPs70nNaMUmgEDFEhnSLmKScTvr+4Q/smHURBffdR/YD8xtsL1u6FN+evTU7E4w2ghcopQgOAQ7ed8R+wYtZ4LYqvxCg6S6XmveY0WTIA4fSHRyamNPkUOLxGQlc4XTyg7vuolevXg22jRs2lPE9vofW7Znft+M4XfH0GzyafoMbdvXYtk1J0X4K8nZycF8Bh/d7KDsA+Zvi2JWbCFQC6zDdFTWtOxZpveLokZ1BVk5/MvsOpG/2aN566yNs20VlpcLlWglAUdHHaOx6QYuua5WpWYHbSrPwfrGDsvfeaxhZ1v/wa/A3PYJh1P3Na18bSuHZsoX4cWObfEh8nz4kFo1j4Cl3YLgDH3M33jgi2JJ08purGFTpYdHsU7g5ycB/7CTSnQ5m9Urjlrfex42zydan4oMH+eODv8fhMHEmuZn7u18Et40YMZy3v/orhiE5NaJ7kkRhEbNc/fvT6zfzyL/tdhJPnEHqeecBUPrWW+y9+ZYGScTB94DWde+I5m5bYKPQmY1nhtWhtNTQdBdKyV9uZd8ji8Hna7Tt0NrVPP+3Q2gr0g2uLTMMg/TMbNIzs2Fyw22e6koKd2+ncM8eDu2roLjQoqTQScHmJGy/AewBYyeuxGKcVdOIjyvE4ark8NZTAPhwy9NHPb698/ukr32FPU//rMOfm9nE3zugdoh/01sHYVIYH8ett97Kg7f9ij/9yWTGjBns37CXLW++TlFcEsw6o9Hjnnjk/3C64/jRtdc2OUHgjlW7+PZpEtSI7kkShUVMS73wQio+Wcb+39xF/PjxAOTP+w0p584k+09/CmlhzKboJgKevYcrmfGHj3hm6IhG+1f7qwGw7Navnlw7z472N36sUTNL7lefVTPQv5feg1PJ6JOI6kLf1N1xCeQMG0vOsIYtHrZtc/jgXgp27aRobzGFO228m5KZ+YPRZA3sic9XTEpKbTdLoOUkkFlS15IS2KJY+fAHjH78pzji4+sC1/otM/Xvq6/mfm3ZgK7br/Z+Dc5eTXeZ1b42yj/dBwZov4Xlt9CWxQG3AxPY5NK8/tvfNmqdM/v1J/Xiy4JFeT0ePnj9NQYOHUaZDcdNGMvZF3+P4aNGN+qaOqNfQrv+HkJ0ZZIoLGKaUorev72bHRd9m703ByZgM9PS6P3b37Y5oKktt+Y/wfssZYBSOJoIKLaXbQSgyFPYZHktvgXNmqDGahzUpKQ7mZT4CnvKLuaj5zejbY0r3kHvQSn0HhIIcFIy40ntGY8rvmu91QzDoEdWDj2ycmAqFOwo5cVNufTI7E16ejLQ/EKljcoy3bh69sRwucJX4SOYGXHsqd5M3v9eCyavG4bBRie81ttm5fjjOa3SwDTNRi1w33vlLXapwN+r+OBBnvvH4xyo9rJ83QYAhowa3Wxi9Nv3NVx2QYjuRBKFRcwzk5Lou2ABOy+7DLRm4L+fw0xO7vDj+GsmqnE0scZQ/8RhAGQ0tWjhUaiaoAaft9E2w2FyfPIzcPUP8PWaSuHOUvK3lbB/ewlr3t+Np7IuEIpLcpKaGU9Kz/h6t3Gk9EwgMdUV9a07tmXjMzzB1qlWaSGhN1zc/VNIG5/D+Psadnnt3H0A69WXeSk7m2lDezb5WE3dog7L3n2bA9VeBvZIo2fPnlRXVTFk1JjmDxzpT3QhIkgpaakR3UD8uLH0XfAnsHWwG6qjWcGgpvHFM94MjL76NG8tLtPJSYMaX5SM3fvJff0Jxp91KS53vS6EYPdT46AmOB++tnG6TfqOSKfviEALhtaa6gofJQeqKD1QRenBKkoOBH72bSmmotgTLMZ0GqT0iAsEO/UCn9TMeJJ7xOFwmm06J+1VUeKhqsyHUlByoIqv+yzFMNuycnYTXUsRsqaiGoXG3TuR3LJK/FpjafBrjV9rvLZmfWI6cUUFbPz0IzZs3AiGg6mnnYlRk7C8ZcuW4P+P/PFb/k4P4ISIFobk1IjuIuWI2Xg7mr8mWdds4oLSMzENgBd3P8gLuxyszPkSt6MuUbk8PY7Bqwpg1R/5suQwM2bfGtymHDV5I56KxgcN5oQ0Hv2klCI+yUV8kovegxov7On3WpQerK4Ldg4GAp/dGw5RerAay1+3dlFSmpuUnvHBrqykZEWiVULGiH4k9E5vcBG1LZu8DYeCLUNxic42X2R/9/A/OGQdDP6uHRqv9gCtzBtpKl8mQvZUe3F7qpn3zLPB+zSK+o3mA4Ds/bt589U1WOlZOF1xvPrY30Iqf4qzmLi41s0DJESsCLzLpaVGiHarbfI0m+jGOXfEZLJTXmfBZ4tYVf4c9hFT6p/0yocU7NlM9Xk/wO+pbLBNxQUu4LrJoKaupaa1HC6TjOxEMrIbz+GjbU1FiSfYslN6MNDac2hvOTvXHKS6wlez50EcVjUJuowkl4/kVJNqVyqPpf2LfsWBhGmH06BnfCb9kvsxKGMAWVkZpNYESEkZbswWupOKKeIH4y5j6DFZaA3vfvEJRnzrP7A0RCioaXzMf08YzOZhPwLAqRSmUjiUwlTgVAYuQ2ECTsuH0qC1HejaVIFV3Fv6sW2bkpfnMjBMrZFCRD2FrNItREc4WpPnxD4DyUnJYlV547lsEtxJ9Oo1mF1NPE7VJLdqj6eJjW0PalqiDEVSehxJ6XH0Hd44IXfXr+ZSsGwVcVf9lJJ95ZQe8lJeabCr0E21M45+DOP2b12FlziKD1Sw52A+uw7n8fa2dyhdX15vTQlIjk8gO6EfA9MHkJOZTUavRLIGppCY6gYFyelx9B4caGlyrTPbNgdLFLXUGEoxMjGE5TscdV1+rUlvrnK7MM3IdBcKEWnS/SREB6ltqTFauHjWzldjNPENvjnKHehK0J7qJjaGJ6g5GqdhkTUwjYHXzWy0rfi9D3jin6/Sp8+PcGYHhjtPYRBwPACWZVN+yENpTZfXgcLDbD+0k9X7v+a97e/jtyw0NtlJ2Vja32B2UNu2MVXbLtjdJc9EteK1JUSscTkMyj2+o+8YRhLUiJhQe+lt6dpZe4FuTWuDcgVyaqIpqAkcs+mvQ444N4bta3a7aRrBJOQcAPpyKmNritRUFHvI31rCl6vWssO7hfjkunYKW2scRlf6yOj8r4zhWeNKiK4h2e3gQHkTrdqdqCt9QgnRrNa01LTm23QwqPG20P1kd3JQo+tyPP7whz/w6KOPkp+fz/Dhw/nld78LbZyqXKlAt9ewqXEMm9qLS/ynYdQbTaaxm11qQgghbN3yZ3BnkE8oERN2FQUSeQ+UNf8tofaCPPGfJ3HWs9eHVrBR093S1GzEEXrz2h4PRpybuXPn8tRTT7Fw4ULWr1/PzTffzLX33svWgiaSmtvAdBjdpttICNF+ttYR74CVlhoRE8o9gXW6PX6r2X2umXw+BZ8c5MuSf1HgXx9awWbN0O8mZhSOGMui0tYsWLCADz74gOnTpwMwePBglr78Mp9//RFh6Xrpaj0rEaiv5NSI7kzr1nXvh4MENSImjO4TmKW4f0bzc6gM6dGLxy74JROffhGnEcIIGKi3TELzwVIkrp5biouprq7mzCPm//F6PPRJdYRvqdwon/m4gQi0MnWrnJpID3MRUcfWOuIfERLUiJhS6bUorfah7cAbLPATSIK1NYHMfGUxo8/p7CvfF/xm7aksA8AsrcSXnx8sz19UEvhPdQlUHKz3Qa4Dv0eCUtg1QdbixYvp27dvcFPlqtW8+K/b5YIjhOh0gY8daakRot2cNZPIXfi3T4+6b9IIeH//v3j/pX8F7zMtzbMG9HzsNbY+9lqjx6ilv4V1c5su0Oy4hRqbSv6dN28e3/lO3UKJymEyNDUFt9tNXl4eJ59ct3RBRdEh0hOdYQlqWipx++oDZA9LIy7R2cJeIqZIvpU4gkZaaoToEGOzU/nH5VOo9lsoFIYKjOYxVCAb3zBqf1cc9v6DzHQPSunglVqjqR62l2E6C4eq97bQNqpoM/EjeoFhEPwWolTg/w43DDyxw57H3Llzefnll1m4cCHDhg3j448/Zvbs2WRmZgaDF21rkl1ubr31Vm6++WZs22bGjBmUlpby4YsvkLu9OGwtNc19XhUXVlJd7sPnsRg6OYvENHdYjt860lolRGeKhtFPEtSImGAYijNG9wpx72ZW6+7b9N1wUhtq1HoV699hwR8f5IOHbmB64gbI38Tg4SafnD6Jv97yY8b94k6UYVK2ZAmJJ5zAvffeS1ZWFvPnz2f79u2kpaUxYcgQRiS7Gkya1xmcLpPRM7KxfDZbVxZQWepj8KSepGa2cp0oIUSXFZjLSoIaIQSw4dlfUu31c+bP/6/B/V6/ZqQrjoJ77q1pLQLXwIEopbjxxhu58cYbg/tW5uby2J8vD18jxVHKNZ0GI47rg21rtq86wLavDlBRLcsGCNEdaGmpEUIAYPmxSwMJyovf+bBB8m/Z83/h8D/fZPhnH2Jm9AZoviXGMGoCj46PagwMbEKbaNAwFEMnZ6G1Zvuu5R1eFyFE9NFaRzzVSibfEyIabHqD0anVuN0u8vLyGDp0aPBncGYafZxOlKp7u7Y0KZ5WsGfuXA69/nrH17OVH1hKKdITIzXHjySyCtGZbB35uZqkpUaIaPDZX0kecRK33jqxUfLv+x+uwFdSwq+No3fjuIcPZ4CzF88bq7H+t4bTlr7ElMtvJn7ChJCr8t7buaRkuxgzdCiJ8ZITI0R3VOHxs2ZPMW6HSZzTIM5p4nY0vK0ddVrL1rq2hzxiJKgRItJK9sDeXPjOU9x7xUWNkn/HJrm5yukMKfnXTEri239/B6u8nOL33+WDtx/nLw/P5px+ZzJgwgmok09k44E9eHxelALTdJDoTMBhmgzo3Y/khER25OcxLKMvL7/1Hj6vBVqhDDi8v7KLLWgphGiLdXtLeG31Xk4dmYXLNKj0Whyq8OLx2VT7reCtZQc+k2o/mqp8Ft+d3C+CNZegRojI2740cDvg+CaTf3fPnkV57jeBtt0QKKcTR3o6Pb/zPb77rVlsX/hnlm98l39/8DZpu09j+DEz6ZGajtbg9VVzqPwwlmXx6uo3GZo6FNOpOGXqNJgahuca4yLd9C5ER/gq7zB3njc60tVoEwlqhIiABpPs7dnF8AyYN+YTvvPd7zbaN2XaKMpzv8FoQ1eQcrkYctOvGcKvSb3x27xSvJ4rXD8ge8JxjfadxTms3LmGFXu+4X9/Wc2J3x9Geq/ENj2/7qo7LZMgk1bHLqUUlq0xIz2TXhtIUCNEBNSfZM/etYy739jIZZddgl55I8eNiENpjVYGKEV1uYe1owewa+bZKNNEq0B7gAaU1jjjsxjgykEpFeii0hplGBSoOCq9VYEDGgbO0p6MHdAb/elyOK5xUAMweeAEJg+cgLfaz+K/reGcH40jPqnjZkzuLLXnQYRPpEe5iPAxVO0Iy673R5agRohOVlFRwYIFC7j70f+g+k3gz2tN3NP6MuLADl7JtfnueXMCVwxtoy0Lu4/Fdu8XTMm5MHCh1vWGVRsmn3/1DWkTh6ItG+UIJBPbXh/l+7IZ2mdPYD/LRtsWk2xN2kWzjlpHV5yD068aw0fPb+ac68aG4SyEl9Y2qgt+y+xSojBoXLHzEIcqvCgC86WomhnFqbnNSHDRK8VNjyR3l2yF6CyGUqH2dkcdCWqE6GQbNmygurqa26/7fvA+pTRYfhImT4YTb6m7HzAB5+F59LjkqibL6+l9jh7X/qDR/Qf+tprMH3+rzfVMyYjD9oc2L03U0aAiMGNFt8qpicKmmpW7DjNrYl80dQvZ1jbaWVpzuNLLyl2HOVjhxbY1lV6L00ZmMaJ3cqSrHlUMFRjJ1BW16l2/cOFCxo8fT0pKCikpKUyfPp233noruL2goIArr7yS7OxsEhISOOecc9iyZUuLZZ5yyikopRr9nHfeecF97r777kbbe/fu3cqnKkR0sO1AoJD1nbtYvmIlG9au4er5v+fqB//Aiy++2ORjivbsDj4uVMrR/ot6amY8+7Ycbnc5nc22rRZbzr945b989dbrfPXW66xa8jpbvvyMw/l7sW2rXUtMdKecmmhsqUlwmfROjaNPajx90+Lpl55ATkYC/XskMKhnIsf0T2fmuD7MOW4AVxw/kOtPHsxHmwsjXe2oYygVjX/ekLSqpaZfv3488MADDB06FICnn36aCy+8kFWrVjF69GhmzZqF0+nktddeIyUlhQULFnDGGWewYcMGEhObTjh8+eWX8Xq9wd+LioqYMGEC3z0iYXLMmDG89957wd9NU6ZeF13PtgPlvLHLANOJv/QAx04IjDBIX7kSlCInJ6fJx2X2H9jqY5lx7W+InXr+IBb/bQ3HzRpCnyFp7S6vs2hb09KEGa6EBCadfX5gX60pP1TEwd272LV2Dbq2e6/mUz17+Cgy+uXgdEXDIp2iIymlGJKZxCur9nD++OxG8650V4ZSWF00qmnVp94FF1zQ4Pf777+fhQsXsnz5cpxOJ8uXL2fdunWMGTMGgEceeYSsrCyef/55rr322ibLzMjIaPD7okWLSEhIaBTUOBwOaZ0RXVpRuYfT//QRLtMgfdq38S57iqefHs+MGTPYv3MH+Vu28bTXwxVXXNF0AdqmsycBd8U5uOBnE/jwuW/YsGwfPfomkZDiwrZ1oCGkpgvC57E6tV5Ho4/SUlOfUorkHj1J7tGz0Ta/z0fB9q1s/GQpli/w5UtrSMrIoGfOQNJ698YIYVLEmBSF3U9tqdHpo3qx+1Alf353Mz8/YziuDmjh7OoMo+t2P7X5q5xlWbzwwgtUVFQwffp0PB4PAHFxccF9TNPE5XKxbNmyZoOaIz3xxBNccskljVp2tmzZQnZ2Nm63m2nTpvG73/2OwYMHt1iWx+MJ1gugtLQ01KcnRIf7zWvrAfjZaUP56X3P89e//jU4yZ4jPo7eAwcz6KpmApoIcrgcnHnVGPZuPsy+LcUk94yjR3YS6LoVphzOKLsQWBaqA4INh9NJ3xGj6DtiVPA+rTUVhw9xMG8neetqWna0RimDxPLydh9TdK4dBytY+k0h5R5/9+o+bIGhVIPxCF1Jq4OatWvXMn36dKqrq0lKSuKVV15h9OjR+Hw+BgwYwO23385jjz1GYmIiCxYsYP/+/eTn54dU9pdffsm6det44oknGtw/bdo0nnnmGYYPH05BQQH33Xcfxx9/POvXr6dHjx7Nljd//nx++9vftvYpChEWD10ykTV7inlm+S4um9a/wSR7v/z3vzAMFyeddFKEa9m8vsPT6dE3iV1rD9JncFqkq9MirXXYWhKUUiRl9CApo+Fnj21b+OO3heWYInw25Zdy3vg+ZCXHHX3nbkIp1WVbalr99WrEiBGsXr2a5cuXc8MNN3DFFVewYcMGnE4nL730Eps3byYjI4OEhASWLl3KzJkzQ85/eeKJJxg7dizHHntsg/tnzpzJxRdfzLhx4zjjjDNYvHgxEMjpacntt99OSUlJ8Gf37t2tfbpCdBinafC9KTkUlXs4XOlrsC3wARL93RhxiU6qKyO1QGXotGWhWsipCccoJcMwccXFd3i5IrwCs7FEX1daJHWb0U8ALpeLoUOHMmXKFObPn8+ECRN4+OGHAZg8eTKrV6+muLiY/Px8lixZQlFREYMGDTpquZWVlSxatCikbqrExETGjRt31JFVbrc7OFKr9keIzqa15sEHH2TgoEH8/JyxVC66hdUfLzliJ7vFlbfb1OoQps/pKEylaETbRzmfQtSwtUamrGmoW89To7VukLcCkJqaCgTyYHJzc7n33nuPWs5///tfPB4Ps2fPPuq+Ho+HjRs3cuKJJ7at0kJ0ghdyd/P61/mseukR8r5ayrjv3ITPl4Jvzzq+d+llnPPZ+4w79lRAUVb2NeP7OCgoDHzTV6hg/75C4dd7I/hMjhT9VwBt2S2OfhKiVqCnsu41vWZ3MUOykkhyd99p3OpmFO56WvVXu+OOO5g5cyY5OTmUlZWxaNEili5dypIlgW+dL7zwApmZmfTv35+1a9dy0003MWvWLM4666xgGZdffjl9+/Zl/vz5Dcp+4oknmDVrVpM5MrfeeisXXHAB/fv3p7CwkPvuu4/S0tLmR4kIEQX+t2YfH63fw753F/GtOxaSNWQcal8pvv4DqNq9gbzPlzBmygloDX3S+zK0lxev90DdFP+1H7Ra40wpwdYWRmvesmH6TDIdCstvY0bxKBGt7a7RpNSlRfb8llT6+NvSrfRLr+vyi3O2vgs3wWXyQu5uqnwWLofBsKxkNu0v5ftT+3dkdbsU1V1aagoKCpgzZw75+fmkpqYyfvx4lixZwplnnglAfn4+t9xyCwUFBfTp04fLL7+cefPmNSgjLy8P44hvUJs3b2bZsmW88847TR53z549XHrppRw8eJDMzEyOO+44li9fzoABA1pTfSE6jd+y2Xu4imPTKnjJ5+GdP/6swfZqj5eCvj35w2VHb5kE2Ld5c9R0pyhDBeaBiWLab7UY1Mgol44Q2XNoGJAa7+Ty6QPbVc7po3px+qheeP02X+UdZsO+0jYFR7HE6MKJwq0Kao4clXSk+qM5mrN06dJG9w0fPrzFpq5FixaFVD8hosV9izey/WAFvZMDAfzixYvp27dvcPvra/bx+cbnW1VmNDUHR09NmqNbTBQWXd/Sbw4woEfrV66vb/ehSj7bdpAKj4XTVBwzIJ0rjx+I0c2TbLpyonD37TQUIoyKK73EO00evPZcXr7XTV5eHieffHJwe59DLhL3tyZxPZoShVXURzXalu6nWHfBhGyeWLYDrXWrWjE/2nyAbYWB+YT6pcdz3vjsbp0/05Rus0yCECI0GpiQk0q/Xhnceuut3Hzzzdi2zYwZMygtLeWdF95g6/518JMOOJjVuZ8+WmtUtDeCHCWokSG8scFlKlozJZHfstmUX8oPTxocNd250UhJS40Qojn33nsvWVlZwdmD09LS6DNkNNnHZXdI+XZVM/PGhOkzybZ012iel4tW2OhWLq4aTl7LJi7E2aM1kBznlIDmKLrykO5o/74lRJdV2xqglOLGG29k06ZNeL1eCgsLuf3hZ+g9tOnFK1vLSHJ2SDmh0rZGRXlQoy0LmXwkzEpDmyk+nM4fn81fP9hClTe0tcfCONF0TOnKicIS1AgRBh39eeCO68H29a82ue3wvqbnsCndUdKxlagn6r/pai1dTGGkDAOSI7/AcHqii2tmDOalr/aEtL9Gy6siBF15nhoJaoToAibNuIWiwq+a3Jae3bfJ+1MGpYazSiHzbG555u9w0LaN3VVX5OsCtOXHe2B7pKsBQEaiC0MpDld4j7qvtNSEptvMUyOECM3/1uwD4JGlW8k5+AlLXniWVz9cxcHicvr3zuD0GZOYeFIiXm8xShkopY74ZlT7fxVsFbH9fjyVFdQOa9I1F23L58Ou9gceUluGobAsG+8R+Ta2rfFW+7Et3Sjnpv7xg//VtTd1+1eWHv3iUZ97+LBA2X4/2utF+/2gdeNvgrW/N3Mb3D/4sHrbj9jXu28fZUVFlB4sbLJOfq+nyfvbrbIIPv8bGA4CfycNyoCMQWA4wTAD25QZmGgl+H9HzTaz5vf6+9W/31FvWxiuzlqD7Qe/B3xV4C0Hb0XNT93/fRXFrPT1p3xtPmP7ptIvPT6irXcXTerLi1/tYc5xLc9dtnZvCf0zEjupVl1XVx7SrXRXbWNqg9LSUlJTUykpKZF1oERYDZ/7Fl6/TXqCk1Pe/S5LNpVz79npDOnh4PNdHm55o5h//yyV6b96qsHFqa7LpPZWByeKO7zTAm968OJeO4ml8ihyeowO/L/mOqqB/aVe/HENv7coA5xuB6apGhxGoah/6GCNVL1OnJr/OFwmvQaG/v6pXLmS6k2bUKYD5XKhnA6Cw6dqj69U3XlQR5wD1bCuqLpAr7nHaG1zwKEgKanJOiX36EnWwMEhP4eQlR+AhB4Nl2jwe6FkdyBYsC3QVs3/7cCttgL3N/h//f2a+F1bHdPH6SkFV3LDAMlwgOkCVwK4ksCV2PjWGY+FwcFyD+v2lrDncFXdw2snwibw1zAMhVlTvsdvNzhUostBaryT1AQnqfFOElwmbodJSZWX5dsPYdU0F7S4LBq1CcAOLprUr8Wn+8Bbm8hOa7gad+3ja//vNA2cpoHDVLhq/u90GDhNFdzmrLetyf0Mo2sk0zdjxc5DJLocjM6OnutkqNdvCWqECKOKigp6piXzwUM/YvpPFgbvv3bWKVRu+5R/f+2V9nARs2xbY2kdDE7cDiMYkGqtKff4KanyBX8qPRZeyybJ7WDa4Azcjs6d2de2NT7bxmdp/JaN1wr83+e38dX+3wr8v3abP/h7vf3sJloi66ndFMpb3zQUcQ6TeJdJvNPE7TSId9b9HlfzE+80cZqq3S1mXr/Nox9tY+bY3gzrldyusjpSqNdv6X4SIow2bNhAtV9z5q1Pwq+fDd7v9VQzqdcRazwJEWMMQ2GgaGrVAaUUyXFOkuOc9Evv/Lo1xTAUbsMkmubi81s21X6bKq9FtS/wU+WzKKn0UeD3BO+v8ln4rKbzyFr6hKkferlMgwqvxQsrd3P9yUM69Hl0lij60wkRe+ya+TwWP3AVfc+7tW7Dupdxf3SvrCQthGiRwzRIMo2wz3qstcZr2VT7bL4zuR+uKF6wtiUS1AgRRqNHj8btUOQVFnPy0KF1G4ozIbVrfmgIIWKPUgq3w+z0Lr+OJkGNEB2lZC8U50Fa3aR6yVpz63QnN//tdezhTweXSfjsv++RtMXPFRGsrhBCxBoJaoToKE+cBaWNJwG791Q3WZPPbrBMwjFDsrhjVNf+RiSEENFGghohOsroC2H53+AHLwV+V4F/lGFyY840bvxzfN2+X/4d3r4jErUUQoiYJUGNEB0lLQeciTDsjKPvq2tn8RBCCNFRJKgRoiP5KmDnMgIz2Bk1w7WbCF52LwcrTLPaCiFENyVBjRAdJS4tcPvP80LbP6lX2KoihBDdkQQ1QnSUCZfAgONrprvXoG0arE9EvS4nbUNSVoQqKoQQsUmCGiE6ilKQ3vKCekIIIcJHZv8SQgghREyQoEYIIYQQMUGCGiGEEELEBAlqhBBCCBETJKgRQgghREyQoEYIIYQQMUGCGiGEEELEBAlqhBBCCBETJKgRQgghREyQoEYIIYQQMUGCGiGEEELEBAlqhBBCCBETJKgRQgghREzoVqt0a60BKC0tjXBNhBBCCBGq2ut27XW8Od0qqCkrKwMgJycnwjURQgghRGuVlZWRmpra7Haljxb2xBDbttm3bx/JyckopSJdnahUWlpKTk4Ou3fvJiUlJdLV6TLkvLWdnLu2kfPWNnLe2ibS501rTVlZGdnZ2RhG85kz3aqlxjAM+vXrF+lqdAkpKSnyhm8DOW9tJ+eubeS8tY2ct7aJ5HlrqYWmliQKCyGEECImSFAjhBBCiJggQY1owO12c9ddd+F2uyNdlS5FzlvbyblrGzlvbSPnrW26ynnrVonCQgghhIhd0lIjhBBCiJggQY0QQgghYoIENUIIIYSICRLUCCGEECImSFAT4+6//36OP/54EhISSEtLa3KfvLw8LrjgAhITE+nZsyc33ngjXq83uH3nzp0opRr9LFmypMVjHz58mDlz5pCamkpqaipz5syhuLi4A59d+HTEeatv69atJCcnN1tWfV999RVnnnkmaWlp9OjRgx/+8IeUl5e349l0nkiet82bN3PhhRfSs2dPUlJSOOGEE/jwww/b8Ww6V6TO3dKlS5t8fyulWLFiRTufVfhF8jUHsHjxYqZNm0Z8fDw9e/bk29/+dhufSeeK5HkbOHBgo9fabbfd1o5nU0eCmhjn9Xr57ne/yw033NDkdsuyOO+886ioqGDZsmUsWrSIl156iV/84heN9n3vvffIz88P/px22mktHvuyyy5j9erVLFmyhCVLlrB69WrmzJnTIc8r3DryvPl8Pi699FJOPPHEox533759nHHGGQwdOpQvvviCJUuWsH79eq688sr2PqVOEanzBnDeeefh9/v54IMPWLlyJRMnTuT8889n//797XpOnSVS5+74449v8L7Oz8/n2muvZeDAgUyZMqXdzyvcIvmae+mll5gzZw5XXXUVa9as4dNPP+Wyy/6/vbsLaeoP4wD+naVTcwydHN8KyxuxTIqFLouErCwS/1AX1eyNrBsZiBRdlJAJXpg1i17I0KZWVOhNIpIpChUuLT1elCiBZigqpsPCyNfnfxGOfG3m2U5bzwe88OfZs9/z5ajP5jmoX1Y/jiJnbgCQlZU145zLyMj4415mIPZPMJlMpFar56xXVlaSm5sb9fT0WNceP35MSqWShoeHiYios7OTAJAoijY/X2trKwGgN2/eWNfMZjMBoLa2tj/uw9GWk9u08+fP09GjRxes9av8/HwSBIEmJyeta6IoEgD6+PHjsnpxJEfnNjAwQADo5cuX1rWvX78SAKqpqVlWL47m6OxmGxsbI0EQKCsr60+2LxtH5zY+Pk4hISFUUFAgxfZlI8f5FhoaSnl5ecvc+fz4nZp/nNlsRmRkJIKDg61rCQkJGB0dRVNT04xjk5KSIAgCtm3bhrKyst/WVavViImJsa7pdDqo1WrU19dL24QMbM2ttrYWpaWluH37tk11R0dH4eHhMeMftnl5eQEAXr9+LdHu5WOv3DQaDSIiIlBSUoKRkRFMTEwgPz8fAQEB0Gq1kvchB3tlN1t5eTm+fPniNO8O/o69cmtubkZPTw/c3NywefNmBAUFYd++ffjw4YPkPcjB3udbTk4ONBoNNm3ahOzs7AX/rLVUPNT84/r6+hAQEDBjzdfXFx4eHta37X18fGA0GlFWVobKykrEx8fj0KFDePjw4aJ1BUGYsy4IgtP8OWAxtuQ2ODiIkydPoqioyOZ/ALdz50709fUhNzcXY2NjsFgsuHDhAgCgt7dX2iZkYK/cFAoFqqurIYoiVCoVPD09kZeXh+fPn9t8bcTfzl7ZzVZYWIiEhASsWbNm2Xv+G9grt46ODgBAZmYmMjIyUFFRAV9fX8TFxWFoaEjaJmRgz/MtLS0NT548QV1dHQwGA65fv47U1FRJ9s1DjRPKzMxc8MK+6Y93797ZXE+hUMxZIyLrur+/P9LT0xEdHY0tW7YgKysLqampuHLlyrLqOpqjcztz5gz0ej127Nhhc80NGzaguLgY165dg7e3NwIDAxEWFoaAgACsWLHC5jpScobciAipqakQBAGvXr1CY2Mj/vvvPyQmJso6DDpDdr/q7u5GVVUVUlJS/ujxUnGG3KampgAAFy9exMGDB6HVamEymaBQKFBaWmpzHSk5Q24AkJ6ejri4OERFReH06dO4e/cuCgsLMTg4uKQ681m57ArM4QwGAw4fPrzoMWvXrrWpVmBgIBoaGmasWSwWjI+Pz5nSf6XT6VBQULBo3f7+/jnrAwMDi9a1J0fnVltbi/Lycly9ehXAzx8GU1NTWLlyJe7du4dTp07NW1uv10Ov16O/vx+rVq2CQqGA0WjEunXrbNqb1Jwht9raWlRUVMBisVhfMd65cwfV1dUoLi6W7M6KpXKG7H5lMpmg0WiQlJRk057sxRlyCwoKAgCsX7/euqZUKhEWFobPnz/btDepOUNu89HpdAB+3kGl0WhsesxCeKhxQv7+/vD395ek1tatW5GdnY3e3l7rN+mLFy+gVCoXvRZBFEXr8QvVHR4eRmNjI6KjowEADQ0NGB4eRmxsrCR7XypH52Y2mzE5OWl9zLNnz5CTk4P6+nqEhIT89jmmf3Dcv38fnp6e2L17tyR7XypnyO379+8AMONapOnPp19Ry8EZsptGRDCZTDh+/Djc3d0l2fOfcobctFotlEol2tvbsX37dgA/7wL69OkTQkNDJdn7UjlDbvMRRREAFv2dYjO7XH7M/hpdXV0kiiJdvnyZfHx8SBRFEkWRvn37RkREExMTFBkZSfHx8dTc3Ew1NTW0evVqMhgM1hpFRUX06NEjam1tpba2NsrNzSV3d3cyGo3WYxoaGig8PJy6u7uta3v37qWoqCgym81kNptp48aNlJiY6Ljml0GK3Gab786A+XK7efMmNTU1UXt7O926dYu8vLzoxo0bdulTanLlNjAwQBqNhg4cOEAtLS3U3t5O586dI3d3d2ppabFbv1KS85wjIqqpqSEA1NraKnlv9iRnbmlpaRQSEkJVVVXU1tZGKSkpJAgCDQ0N2aVXKcmVW319PRmNRhJFkTo6Oujp06cUHBxMSUlJkvTFQ42LO3HiBAGY81FXV2c9pquri/bv309eXl7k5+dHBoOBfvz4Yf16UVERRUREkLe3N6lUKtJqtfTgwYMZz1NXV0cAqLOz07o2ODhIycnJpFKpSKVSUXJyMlksFjt3LA0pcpttvm/4+XI7duwY+fn5kYeHB0VFRVFJSYnE3dmPnLm9ffuW9uzZQ35+fqRSqUin01FlZaXEHdqPnNkRER05coRiY2Ml7Mgx5MxtbGyMzp49S4IgkEqlol27dtH79+8l7tA+5MqtqamJYmJiSK1Wk6enJ4WHh9OlS5doZGREkr4URETLf7+HMcYYY0xefPcTY4wxxlwCDzWMMcYYcwk81DDGGGPMJfBQwxhjjDGXwEMNY4wxxlwCDzWMMcYYcwk81DDGGGPMJfBQwxhjjDGXwEMNY4wxxlwCDzWMMcYYcwk81DDGGGPMJfBQwxhjjDGX8D/0GV2iPYdUCQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "intC, envC = 0, 16\n",
    "print(\"confirming we have a clean boundary for counties\",intC,\"and\",envC)\n",
    "for v in countyTractList[envC]:\n",
    "    if tractGeom[v].intersects(countyGeom[intC]):\n",
    "        plotPoly(tractGeom[v])\n",
    "        plotCenter(\"e\",tractGeom[v])\n",
    "for v in countyTractList[intC]:    \n",
    "    if tractGeom[v].intersects(countyGeom[envC]):\n",
    "        plotPoly(tractGeom[v],0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a6c93c4-af08-47d5-90f7-dc0b4513aad5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last chance to alter the skipList, otherwise the above 0 units will be axed\n",
      "here is the proposed skipList []\n",
      "here is the final skipList []\n"
     ]
    }
   ],
   "source": [
    "print(\"Last chance to alter the skipList, otherwise the above\",len(skipList),\"units will be axed\")\n",
    "print(\"here is the proposed skipList\", skipList)\n",
    "#skipList = [] #...  #alter here if needed\n",
    "print(\"here is the final skipList\", skipList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2989f381-466b-4882-bf1d-cfa37a7ba8ef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now preserve the original county unit lists and geoms, then rebuild as needed\n",
      "Here is the revised state county map after eliminating coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excellent!  We have no populated islands.  SKIP the below code block.\n",
      "we will scale longitudinal distance by 0.77769\n"
     ]
    }
   ],
   "source": [
    "print(\"I will now preserve the original county unit lists and geoms, then rebuild as needed\")\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "trueCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    trueCountyTractList[c] = countyTractList[c].copy()\n",
    "    if isAlteredCounty[c]:\n",
    "        print(\"removing coastal units from countyNo\",c)\n",
    "        countyTractList[c] = list()\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in trueCountyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                countyTractList[c].append(t)\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            print(\"Uh oh! county\",c,\"didn't have any usable tracts\")\n",
    "MAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c])\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "origPopMAP = MAP   #origPopMAP is the map after eliminating coastal unpopulated tracts, with original islands\n",
    "print(\"Here is the revised state county map after eliminating coastal tracts\")\n",
    "plt.show()\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    print(\"Excellent!  We have no populated islands.  SKIP the below code block.\")\n",
    "else:\n",
    "    print(\"We appear to have some populated islands.  Separate out the main state geom in next block.\")\n",
    "LAT = MAP.centroid.y\n",
    "xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "print(\"we will scale longitudinal distance by\",r5(xScale))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "62d8bf69-9572-4c58-b774-ac48baf89ad2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "vtdGeom = tractGeom.copy()\n",
    "nVTDs = len(vtdGeom)\n",
    "aDP = float(statePop)/nDistricts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8a562a21-4107-4a3c-a320-90442a473387",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\n",
      "unit 3739 is a true island.  We will move it to adjoin the mainland in same county.\n",
      "unit 3759 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 3068 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 3097 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 1006 is a true island.  We will move it to adjoin the mainland in same county.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#RUN THIS ONLY IF WE FOUND POPULATED ISLANDS\n",
    "nSubGeoms = len(MAP.geoms)\n",
    "subGeoms = [MAP.geoms[n] for n in range(nSubGeoms)]\n",
    "subAreas = [subGeoms[n].area for n in range(nSubGeoms)]\n",
    "mainSubGeomNo = subAreas.index(np.max(subAreas))\n",
    "mainGeom = subGeoms[mainSubGeomNo]\n",
    "nonMainGeom = dummyPoly\n",
    "for geo in subGeoms:\n",
    "    if geo != mainGeom:\n",
    "        if nonMainGeom == dummyPoly:\n",
    "            nonMainGeom = geo\n",
    "        else:\n",
    "            nonMainGeom = nonMainGeom.union(geo)\n",
    "        \n",
    "print(\"Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\")\n",
    "hasIsland = [False for c in range(nCounties)]\n",
    "isIsland =  [False for t in range(nTracts)]\n",
    "islandXshift, islandYshift = [0. for t in range(nTracts)], [0. for t in range(nTracts)]\n",
    "islandList = list()\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(nonMainGeom):  #this county contains an island.  Find all its island tracts\n",
    "        hasIsland[c] = True\n",
    "        mainCountyGeom = countyGeom[c].intersection(mainGeom)\n",
    "        plotPoly(mainCountyGeom)\n",
    "        plotCenter(c,mainCountyGeom)\n",
    "        for t in countyTractList[c]:\n",
    "            if tractGeom[t].intersects(nonMainGeom) and t not in skipList:\n",
    "                if tractGeom[t].intersects(mainCountyGeom):\n",
    "                    print(\"unit\",t,\"has island pieces.  We will reduce the tract to its main state component\")\n",
    "                    plotPoly(tractGeom[t],0.2)\n",
    "                    tractGeom[t] = tractGeom[t].intersection(mainCountyGeom)\n",
    "                    tractCP[t] = tractGeom[t].centroid\n",
    "                    tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                    plotPoly(tractGeom[t])\n",
    "                    plotCenter(t,tractGeom[t])\n",
    "                else:    \n",
    "                    isIsland[t] = True\n",
    "                    print(\"unit\",t,\"is a true island.  We will move it to adjoin the mainland in same county.\")\n",
    "                    islandList.append(t)\n",
    "                    if tractGeom[t].geom_type != dummyPoly.geom_type :  #island tract is multiple geoms.  collapse to its largest isle\n",
    "                        isleGeos = [geo for geo in tractGeom[t].geoms]\n",
    "                        isleAreas = [geo.area for geo in isleGeos]\n",
    "                        biggestIsleNo = isleAreas.index(np.max(isleAreas))\n",
    "                        tractGeom[t] = isleGeos[biggestIsleNo]\n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                    p1, p2 = nearest_points(mainCountyGeom, tractGeom[t])\n",
    "                    islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "                    plotPoly(tractGeom[t])\n",
    "                    plotCenter(t,tractGeom[t])\n",
    "                    plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                    tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                    tractCP[t] = tractGeom[t].centroid\n",
    "                    tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                    plotPoly(tractGeom[t],0.2)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9a94118d-5863-4458-b77a-67d18cf01c2c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\n",
      "This is not appropriate for large islands like Michigan UP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with island triage - RUN ONLY WITH ISLANDS\n",
    "print(\"If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\")\n",
    "print(\"This is not appropriate for large islands like Michigan UP\")\n",
    "for c in range(nCounties) :\n",
    "    if hasIsland[c] :  #rebuild the county geom with the translated islands\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in countyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "MAP = countyGeom[0]\n",
    "plotPoly(countyGeom[0])\n",
    "for c in range(1,nCounties):\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "    plotPoly(countyGeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4aebe4ee-ee7b-4bf3-8413-f315556d453e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing all county centerpoints, then plot them\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"computing all county centerpoints, then plot them\")\n",
    "countyCP  = list()\n",
    "for c in range(nCounties):\n",
    "    cTL = countyTractList[c]\n",
    "    countyCP.append(getHDcp( [tractCP[v] for v in cTL], [tractPop[v] for v in cTL], [i for i in range(len(cTL) ) ] ) )\n",
    "    if countyCP[c].disjoint(countyGeom[c]):  #possible with weird-shaped county\n",
    "        countyCP[c] = nearest_points(countyGeom[c],countyCP[c])[0]\n",
    "    plotCenter(c, countyCP[c])\n",
    "    plotPoly(countyGeom[c],0.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cb3fb231-f24c-4283-bb8b-587df2f19cf2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the map topology before any squish operations\n",
      "Working on county  0 distances\n",
      "Working on county  20 distances\n",
      "Working on county  40 distances\n",
      "Working on county  60 distances\n",
      "the max LAT-scaled distance between counties is 6.0071\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter user-picked max district diameter, or 0 to accept 6.0071  6.01\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on county  0 neighbors\n",
      "Working on county  20 neighbors\n",
      "Working on county  40 neighbors\n",
      "Working on county  60 neighbors\n",
      "I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#CHANGE- do not use clipLines to find outcroppings.  Instead, find boundary counties with low neighborcounts\n",
    "print(\"Now finalize the map topology before any squish operations\")\n",
    "preSquishCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "maxD = 0.\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"distances\")\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "    plotCenter(r3(countyPop[c]/statePop), countyGeom[c], 7 )\n",
    "    for cc in range(c+1, nCounties):\n",
    "        dist = getLongDist(countyCP[c],countyCP[cc],xScale)\n",
    "        if dist > maxD : #and cc not in cutCountyList:\n",
    "            maxD = dist\n",
    "            #print(c,cc,maxD)\n",
    "print(\"the max LAT-scaled distance between counties is\",r5(maxD))\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAP.centroid.buffer(0.5*maxD))\n",
    "plt.show()\n",
    "inputD = float( input(\"enter user-picked max district diameter, or 0 to accept \"+str(r5(maxD))+\" \") )\n",
    "if inputD > 0:\n",
    "    maxD = inputD\n",
    "\n",
    "neighborCountyList = [list() for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"neighbors\")\n",
    "    for cc in range(nCounties):\n",
    "        if cc > c :  \n",
    "            if countyGeom[c].intersects(countyGeom[cc]) :\n",
    "                neighborCountyList[c].append(cc)\n",
    "                neighborCountyList[cc].append(c)\n",
    "print(\"I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\")\n",
    "hasFewNeighborCs, has1neighborCs = list(), list()\n",
    "plotPoly(MAP,0.15)\n",
    "for c in range(nCounties):\n",
    "    if len(neighborCountyList[c]) == 2:\n",
    "        hasFewNeighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.2,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.5)\n",
    "    if len(neighborCountyList[c]) < 2:\n",
    "        has1neighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.1,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "plt.show()                      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "207f3a55-e361-4777-ae46-41fe3d54a4b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MOVE NCUTDISTRICTS (district slice-out) code UP TO HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0062ac21-3328-4616-99ed-70c53e62b308",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d63e9f85-336f-4e38-8ed7-75035e9845f4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing from above, develop corner county blocks from each low-pop corner county until it hits 0.125 of 721714\n",
      "checking if county 41 with pop 13292.0 and 1 or 2 neighbors is less pop than 90214\n",
      "checking if county 58 with pop 2404.0 and 1 or 2 neighbors is less pop than 90214\n"
     ]
    },
    {
     "data": {
      "image/png": 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ODq688krX9Lx59oFJZ82a5dN4PJ4wGgxQlQ644vI7A7ofb5WV/YjPPpsFg2LQNB9sw+KB1ja+QyDaOOiVwdVxnH4/vw6de6DCBKBLgt/SrN2VuZTSL92bC5MJHe65B5ASlv37fU6PyBMt2TN/IAYP9ESptQwHrHHQ8aFKcwxYPNSa/oZqtnHo27cvFi1ahOTkZCxdulTrrPmdcN4lpOq3HxZFKFAVwGDwvcKzQ4cOMBgMdWpTTp8+XafWpblMSUn2bvufeBK20jK/pElUn+9LL0JFaNz08Ph363EW7RBj8K02WMuhBQKNAYsHWtNdQs42DhMmTHCb7482DnpkCILbmnesfQ2RFkA1+v51DAsLw5AhQ7ChVn8pGzZswMiRI31OHwCUsDB0eX4hbGfPonzH//ySJlF9jl+0AACuaBejcU4C76JNIhwX8cawTJ/S0XJogUBjGxYPtKY2LIFu46A3ro7jdBywxPz5eQDAiPsf90t68+bNw4wZMzB06FBkZGTg1VdfRV5eHu655x6/pA/YG+AKkwll3/wfYmpc7yfyJ6vj+kgHU+s/VUkp0VEUI8oU4VM6mZmZyMz0LejRq9b/V+AnrakNCxC4Ng564+o4TqeNbisrLsImgMNXdEffBP80YJ02bRrOnTuHxx57DPn5+ejfvz8+/fRTpKSk+CV9ABAGA9r8ciqKP/4YHX9/Hwxt2vgtbSInq+O4a1Ja37GprtZ1jgkEXhLyQGs6j7dEGwc9URRHx3E6DTgP/m8dDBKIqvJv6/vZs2fj2LFjsFgs2LlzJ8aMGePX9AGg/d13w1ZUhOJ1n/s9bSIAqHTUsJha00G4UaFSzuZhwOIBAQEpW8cfUku0cdCT6ktC+mx022vYeAAIyt5jTQkJCE9Lw/kA3z1BocsqJcKEaJW1v3XV7i+FamPAEoLmzZuH119/HW+++SZ++OEHzJ071+9tHPTC1ehWh/cKqqqKHwcPAwBE3DpV49w0T8TQIa2nRTrpTqWqwhgSl4OA8ovHodosWmdD19iGxQM2VUJpRV+almjjoBfOX2aqDmtYzu/d6eoBe+zN87TNTDOZEhNhzcuDrbgYhthYrbNDrcxX50tQbtNn+zN/U20Xtc6C7jFg8YAqZauL8mfPno3Zs2drnY2AeC3nE3x/5jBUKbHvwk4A0GdnTJ3tgxzm33oF+mqcleaKueoqnH3pZRyfPh3dVq6EEh6udZaoFfmpwqp1FlpMVPQlUC76NjQHoO3QAoHGS0IeaK130LRWi/c+gi9Pv47/FryLgspvIaraoktsO7+lv2TJEnTv3h3h4eEYMmQIvv7662al06FTCn7uEQt88X9+y1tLC+vaFYnPPAPLocOwHDqkdXaolbk5oR3aGrXtDj7Y5OTkID09Henp6QDsTQDS09PxyCOPaJwz37GGxQM2Fa2uhqVVkwpGtbsN/5z0B78n7RzWYMmSJRg1ahReeeUVZGZmYt++fc369aJU2mBpE+n3fLakyGFDAQCWgwcRcemlGueGWhv+VvSOc2iB1og1LB5QpYSBAUtwCdAX1t/DGlREGBBRVOHnXLYsQ0wMIgYOxJmXXoatpETr7BAFKZ5jmsKAxQOqbF2Nbls/EZAumAIxrEHEhHGIP23Fybx9/siiZuIffhhV+fko27JV66wQBS2eZRrnU8CSlZUFIQQeeOAB1zwpJR599FEkJiYiIiICY8eOxffff99oOsuWLYNw3Gtf81FRoY9fnja19TW6bU3e/+5rTM7+A36xfC4mLX8AUgSmoV4ghjW45LpbUBYOfHv/nUFdjRvWzX6HmXqxXOOcUGsSvN+I5gq9Enuj2QHLjh078Oqrr2LAgAFu85955hksXLgQL730Enbs2IGEhASMHz8eJU1UFcfGxiI/P9/tEa6TOw5UKV0dkJH+vJG7HD9e/Ao/lR/AzxcPIlwmY3TXIQHbnz+HNejSYwBK7roJKfsvYNOrj/ohd9owREcjrHt3XNydq3VWyAeVtkqcu3gO5y6ew/mK87hQcQEXKi6gsKIQhRWFKLIUuR7F1mKUWEtQYi1BqbUUZZVlKK8sR0VVBaw2K6rUKr8E4SJk6h1CpZzN16xGt6WlpZg+fTpee+01/P3vf3fNl1Ji0aJF+Otf/4qbbroJAPD2228jPj4e//73v/Hb3/62wTSFEEhISGhOdloEK1j0S5U2RKEbtt/xQUD3E6hhDQbfch9OvvgBLmz5GvLu4LwjTVqtsB49CuvRoyhZtw6Rw4cj8ZmneZtzkPndF7/D9oLtfk1TQMAgDFCEAoNiqJ5WFBiEAecrzgMAOkR0gCpVSCkhIaFKFRWqDbDZ0P+IhL32QTrap0kAKiDC8I+r38I1ia2ksTcrWBrVrIDl3nvvxcSJE3H11Ve7BSxHjx5FQUGB2zV+s9mMK664Alu2bGk0YCktLUVKSgpsNhsGDRqExx9/3HVbltaCuao+FKhQIVqgOVbNYQ1uvPFG1/wNGzZg8uTJzU43rn1nrB/ZGf235GPzZ6/iiusa/p7olskEc2oqbKWliM3MxIV//Qv5jzyCLs88o3XOyAvnKs7hiqQrMCV1CqTjP+dJ1DUNuIIK53znOqpUoUKFKlXYVFv1tKrCJu3TNmmDlNI1vffsXmz+aTNu6X0LhBBQhAIB+/NFVeJgmQWAgBCK41lAQEGRtQTbj7yOg4U/t56AhRrldcCSnZ2NXbt2YceOHXWWOX951neN//jx4w2m2adPHyxbtgyXXnopiouL8cILL2DUqFHYs2cPUlNT693GYrHAYqnuxri4uNjbonhMgrfW6ZkqbS0SsAD2Pg1mzJiBoUOHIiMjA6+++qpfhjX4xdKPcWTgEJRu3w4EYcAihEC3le9DKApEWBhsFy6gaPVqJD7xBITJpHX2yENCCHSJ7oIru16pdVaadKAoH1OPvI5KHfZi3Tw8yTTFq4DlxIkTmDNnDtavX99o+xJvr/GPGDECI0aMcE2PGjUKgwcPxosvvojFixfXu01WVhYWLFjgTfZ9EjrXUYOPlCoU0TKdSwVqWIO843sBAOUl5/2RTU0o4eGwVdlwctNe5J7qggsZj6DwkzwMvCoZkbFhWmePPBBMx7kwxf6dr1RbR8ASPO+8drz6Wbpz506cPn0aQ4YMgdFohNFoxKZNm7B48WIYjUZXzYqv1/gVRcGwYcNwqJGeM+fPn4+ioiLX48SJE94UxTu8IqRrLXVJyGn27Nk4duwYLBYLdu7ciTFjxvic5oFFTwIA+ky7y+e0tGKzVmLFb7OxdvkZ/GzoAUPbtvj2vyfw1p++wYcLd2mdPWplwhT77+2qVhKwUNO8qmEZN24c9u7d6zbv9ttvR58+ffDnP/8ZPXr0QEJCAjZs2OBqf2K1WrFp0yY8/fTTHu9HSonc3Fxc2kivmWazGWaz7+MueJQf1K01Iv2w1+AFd5dC4UlJAA6ipCCAgXeAHV69BRdMnTGgaxEuu3c8zHHRqCirxAfP7cLPBwthvViFsAh2rk3+4axhqeIloRYhdZA/r44eMTEx6N+/v9u8qKgotG/f3jX/gQcewJNPPonU1FSkpqbiySefRGRkJH71q1+5tpk5cya6dOmCrKwsAMCCBQswYsQIpKamori4GIsXL0Zubi5efvllX8tHIUCFDcYgH2Ui494F2LdqP059tRNofvtdTVlLKwCYMHDGaJjjogEA4VEmDBqXjK/e2w/FqP0Bj1qP6hqW1jSas/bV+dJ1F5b9crtNlai0VQaq83Cv+P0o/6c//QkXL17E7NmzceHCBQwfPhzr169HTEyMa528vDwoSvUv4sLCQtx9990oKChAXFwc0tPTsXnzZlx22WX+zl7zSMlGtzompQqhBHcNS1RcB/xv2F+BCuC7pR/ikl+NQ1hcTNMb6kh5YQWEVBDWJtpt/vdf/4wOSdEwmjiIHflPmOM7H71tMb7d9ob9ziJHPYCocQu0cNzPJGTNeXDdHu3qF9s57Tozy+ptHMtrposaaQpICKkCkFCkc7p6vnDux2rDA+p9+B/SHHuopspIGFCF9I3LUXNhdQ4FpHSv6ag5LWXNHr6FI4vOHAtXmq70aq/vSMO+Wt3jaVfDneg7FGjTpoEPpAX4HLBs3LjRbVoIgUcffRSPPvqox9s8//zzeP75533NSsA4/1hInyRUKK1glIlKcylMlmhs2hOL8wWfYMyCW7TOkldKz5dDIgqKqD4MqjYVp/NKMHBcsoY5o9bI6Khh6SjLYQmLd/TMImBzu61TAMIeLtjnCcehvMY0UGNZrWcISOcmUByza9xe7VpfsW/jvDQthP2kLwSkY30IgVHfLsGwiHxUdb+ieteOnKq2CsSp+UgyVcHZ/FlAusoihH2ugHTc2m2fKVzZd24DR96caTteu5YL19vjbOqgiJrrOfdTvc25coGPt5tQgW4+fWa+Cu569JbEeEW3VKlCtNBdQoFUEVsKpVTCcDEGbTs2fFdN4YHjyFm2FUNmjUTbPt6PEB0ocV3aAucUlOefQ1hqkmt+u85ROLL7DC67vjvCwnnIIf9wnmzbpl6BYRP0+4O3Juu3ryK9cxz+cHPgeuIOhMOnS/Dx9o80bysY/D9LWwgvCelXa6lhgQQqOpYiQi3F0T1n613l4tkirH5mBw5c6IR1z25u4Qw27OvHVmL7t2GIuHgGcb26uOYrBgXX3t0fFWWV+L//HNYwh9TaGBw/UtQganSrQLaKH1daaQVH+ZbBeEW/JFQoQX6XEOC49KgAKR0v4qTsgp/+uxsXz1ePwXVy2368+dBOlJvawVRVhvOmRFRZAjPQo6fKzxRi48PZ+PZkewBAvwHhde6oa5sQhfTxXXHwfwXsNZr8RggBISVsQXRbswIVwhD8xyqtsH7WAxI8yOqZPWBpBb9aHH9ml94wAPvfyMea9y8A7+9AjOUU2rcDCosAGOORnnIBsrIKuSej8MXDH+DaZ1qmrUvF6fM4uHYHugxKRvuh9kaDB1ZuwfdnOqGTcgq/yPoFzHFR9W6b0DMOVVYVh3NOI3VY88ddIqrJAPsl4aAgpb2GRWkFxyqNMNTzgJS8JKRnraWGxdnorePQPhiUfB5RKMXAbsUIN1bhWFk8Co3xSI07hZHzp2D4n25AnKUAxy7E4uLZIrdUpCpRkX/arfZFtVai8PvDOL5uB0p/Ou1VrqylFdjxzEos++t2fJ1jQvbrBfj43rdw/JOtMCj2KKt9p7AGgxUASOrdFp26xeKrd/fj7E+lXu2fgtfmzZsxadIkJCYmQgiBDz/80K/pKwBswfKD0nlnUas4VmmDNSwU9KyG4yi0BcmvrEYICcfNBAKj/joVoxzzVVXFiS934/jXBzHwN1cBAIzhZgwd3xlfbpZYe+87iOwUh+h2EYhpY8SevSoqwtoi0laEXz5+BaIT2mHdvHdxtMo+fEDEik349fOZdW4/runA+19j55f5MJiNKCo3odLYHokRpxEXZcPR05HIr2yH4x9dBBCBWOsp9JvceBcEQghMnD0A7z+5A2sX5yLjhh64ZFgCDCYevPXEavPvJcaysjIMHDgQt99+O6ZMmeLXtEtLTsIqRNDUsOz6+J8YDLh16UHeYcDiCRlcY2yEkvJK+wCYxWrw9hDrJAGIvGj8Y+F7+MO86a75iqIgZfwQpIx3v7Og102X48DW9/FT236IKsrHT5ZYqKdMiJUF6NXlAn7Ii8CKhzZh1IT2OFqVApO1BN07luFgUQJy/rkeI/9yEwCgNP881v5tPayqCWNv6YX9n+7Bj+VJgOgAWIEkUx4GT2qP5OuqLz1ZC0vw4Z/W4Cw64do/j0XH3p2bLF9kbBhu/EM61izKxX/f2Y+Th4swbmZf/7x55BfF1mJEmRquKfNWZmYmMjMz/ZZeTV/vehUA0KVtr4Ck728dcl8CAHRM1Un/YkGIAYsHOFqzfs377EUAwODoWzXOie9SR7fH4Y3nYf6xrUfrG8NNmPTCrbj402lEdb0KZ3b8gKL8EqRcPQWmSDMSV2/B1x/n48v/VgEAuncowfinf43y+/+NPT+2w4XbFwOxbXDugkB5WHuEVxXhk/+cA5CE9B5FGPGHX8BSVI6IdlfV2XdYmxj88pXpsFmqYAz3fDTmuI6RmPF4BrZ/dAQ7PzsOo1FB+jVdEds+wuM0KLDCjQ0PbKsnVVUXAQCjBt+tcU48o0LBtvhbMGLQSK2zErRYN+UxRix6VGGzQKoGvDb5z1pnxWdTMyegXT8TvOmeW1EURHVNAAB0HNYXvX5xGUyR9jG2Um8cidteuxHDepci1lCCjPsnAACueeQ6RFvP4oQxFWfKIlER1gZXjFAx7clx6NqmGF2TgJF/uhGKwYCIdg33tiuE8CpYcW2nCAyf1AOjpvbCd5t/xvtP7PA6DQoMKWXw1Cb/lAMAEEF0l1Cw0/qHO2tYPCClHoZ9ovoYFSOEDEeYsXW0vJeQkH78Y1MUBZfN/QVqVkKHd2iD6a/+ElIChnD3AUQnPXWD/3beCKEIDLq6K04fL8GhHafwv4+O4LJJPVpk39S4YBnoVXZIBc6ehjC0zCC4pD3WsHgoWL7EocakGCDRin5hSdc/AaWYzXWCFS1c+es+AIBvv/pJ45wQEFxdOMjwOPsLA393hwoGLB5gqKJfRsUIiOC4S8ATodaxmslsgNFsgKW8CrZWcKdXsAuqgMWZ12C6TTh43l5dCqJPWjshdg4JKibFBIhWVMMCgVA7ql05vTcAYOdnx1FpbU2fZfDxdxuW0tJS5ObmIjc3FwBw9OhR5ObmIi8vz/fE2a9JyOEn7YFg+tURasyGMAhhQ6WtlZzopH/bsASDrv3aI6lPW+z45Cg+eiE35GqZ9EQ6RgL2l5ycHKSnpyM9PR0AMG/ePKSnp+ORRx7xOW3p6H8laBoJk88YsHiK3wldCjPa71Jx9scS7ELxXB0eZcKk3w8EJJD/YxHyvj+vdZZCmj8DgLFjx0JKWeexbNky3xN33B3E9oWhgwGLhxjF65PZEAYAuOiPgEVKSJsNtiorqiovotJaBqulBJaKQlSUn4dqq/R9H01nAqF2SQgAfj5YCAAYOC4ZSX0964eGAiCIOsmUjlGagyW/dsH53T56thwAsPenoibWDCw2r/bAeOuXGLPrUfy4x/nFqP6CNHXDsxTVX6fa69acrrflgqh/P6KJtJyve1f+AAUqjhu7oVxx74Zd1PvFkfbu4R15qbtO9bSQ1RfKaq8nnCddWb3MOU9VVcBxm7isMV849i2EhOIouhQGVIkw2BQTbEoYbEoYpGKfrhIm2IQRyfIo0B644T+jEW3fJVQAqnCe+iVUxx5UxzLUWcc+LZv4pTZYhuHt23Y2uo6vpASkCM6Dmi92rjsOABh2fXcYOJqtZoLp8rczr8FTwxIs+awrKszebUT7aG3vLGTA4oHhYUfRxiBwPCa91tdZur0Utb/uNSacJ263k3wDK0s0HhC41pU1p52BARwBgcQpUYbO1mMoDu+CCiWygSBHos4Xye0AIFxPokZOnEFT9aqixpOwpy2Ee9pCgRACZqPBvkwI+68jUb2uCoEqVcKmSkhbFWCzQFRZIVQrFJsVwmaFsbIEkaiEQVahtxKGGcVWhCemwqAYoQgBIRT7M+z7U6BAcezbvkyBgGMd5zwo1dsJBQLCsY0CQOCfR9fgqGgdl52asmTJEjz77LPIz89Hv379sGjRIowePTqg+yw9XwEAkLbgOWG2Rv5uwxJIoXj5VCtto+w12cntIjXNBwMWD0SZjYjvcRUSJi3UOivNcqnWGQiwlhiZ43jhYXx44bvA70jjg/CKFSvwwAMPYMmSJRg1ahReeeUVZGZmYt++fejatWtA9llVaUN5iRUDxyUjPNr7nnPJf4KpwXPw5DT4Of8stA5lWfdK5IGWuk5eabVpek1+4cKFuOOOO3DnnXeib9++WLRoEZKTk7F06dKA7dN60YbKChvCwltHb8XBLljahEhIiCAKsMh3DFiIPNQSh8aKH40w2LSpZbBardi5cycmTJjgNn/ChAnYsmVLwPYbGRuG6LZmHN55OmD7IM8E0yUhiGAJrchfGLAQeaClDuJqeBUq2l1okX3VdvbsWdhsNsTHx7vNj4+PR0FBQUD33blXG3YaR17iGG+hhgELka5IKFHadlFfOziTMvC/upP6tEXpeQs+WpyLE/vYD4tWgmm0Zim1b1NBLYsBC5EHgqaa3AcdOnSAwWCoU5ty+vTpOrUu/pY2KhET7uiH4nMV+OilPSi9EBp3ZOlRsPytB2PrlWDMs54wYCHySP0917QmYWFhGDJkCDZs2OA2f8OGDRg5cmTA9586LB43zE2HVCXy9p0L+P6oruDqh4VCDW9rJiKXefPmYcaMGRg6dCgyMjLw6quvIi8vD/fcc0+L7N9WZb8cVsX2LJoIqktCQdiGhXc1+YY1LEQea/0Hm2nTpmHRokV47LHHMGjQIGzevBmffvopUlJSWmT/R/ecBQD0HNypRfZH7oKthiWYApZAhVebN2/GpEmTkJiYCCEEPvzww4DsRw9Yw0Kt2887gfWPAGqlo/cj2fAzUGMeaq1zATIiNL4us2fPxuzZszXZd2ScvUdNZ00Ltayguq0ZQAiOYlFHWVkZBg4ciNtvvx1TpkzROjsBFRpHYKpDi+7XNZG3DcjbCgy8xTFDuIYPcA0d0NQzAFF+GLCc1KAAoeViiRUAEBWr7ZgloSxYLgn5avPmzXj22Wexc+dO5OfnY/Xq1bjhhhu0zpbXMjMzkZmZqXU2WgQDlhCkRffrmjJFADcs8S2NPf+E3J/tn/xQvaSU+HrFIRhMCgwmXq3WRBCN1uyrUKqZ8BetK7QYsISgmt2vA8CiRYvw+eefY+nSpcjKytI4d/oUKgdxLeV9b+9/5bJJ3TXOSegKtktCvgilmglf6eVPwqefMVlZWRBC4IEHHnDNk1Li0UcfRWJiIiIiIjB27Fh8//33Taa1atUqpKWlwWw2Iy0tDatXr/Yla/6nl0/MR1p1v94aBFODxGDUsWsMDCYF+YcKtc5KyAq2v3HZOg7L5KFmByw7duzAq6++igEDBrjNf+aZZ7Bw4UK89NJL2LFjBxISEjB+/HiUlJQ0mNbWrVsxbdo0zJgxA3v27MGMGTNw8803Y/v27c3NHjVAy+7XteP7US1UfnVqyWAUUBQBxcjLQVoJptGa+Z0MPc06MpSWlmL69Ol47bXX0LZtW9d8KSUWLVqEv/71r7jpppvQv39/vP322ygvL8e///3vBtNbtGgRxo8fj/nz56NPnz6YP38+xo0bh0WLFjUne+QBLbpfJ6rPif3nsevz41izKBdSlci4safWWQppPA5QffQQyjarDcu9996LiRMn4uqrr8bf//531/yjR4+ioKDA7XKD2WzGFVdcgS1btuC3v/1tvelt3boVc+fOdZt3zTXXMGAJAC27X9dEYR5QVeFzMgIC5yvOo9JWCZMhkKMpCyj5MbBUWmA2hcadMmsX5QIA2iVGYdxtaWjTKVLbDIUwCYkTxSew69Qu1+UhZ61L7ctFtefXXr++tOuoqgTO7ANUtdH1ZD3Ljpz+Vh9nUQ8Uni1Ad/U4TmG439MuLS3F4cOHXdNHjx5Fbm4u2rVr59ebKPQQxnodsGRnZ2PXrl3YsWNHnWXOk2B9lxuOHz/eYJoFBQVeX6KwWCywWKrHGykuLvYo/6GuZvfrN954o2v+hg0bMHnyZA1zFiBVFfY+WHwUHRYNAPj27LcYEj/E5/QaIsJtiDgXgw1fb8X1V40N2H70RAig24AOuO53A5pemQIqxhSDt75/C299/5bWWfFIpyAJWPZ/8hJGAJBxyX5POycnB1deeaVret68eQCAWbNmYdmyZX7fn5a8ClhOnDiBOXPmYP369QgPD29wveZcbvB2m6ysLCxYsMCDXFNtWne/3qIUExB/qc/JjEocBQBQZWA7NPvNfZlYOX8PKizWgO5HTzp1i8W5n0u1zgYB+Pimj1FoKQRQfWec67nG8bj2suqnuuvWVOduu13/ArYshpj1UePr1dhHzeUxMV0aL1AjWqpmAgCErMR5xCDj14/4NV0AGDt2bFC1PfKFVwHLzp07cfr0aQwZUv0L02azYfPmzXjppZdw4MABAPYak86dO7vWaepyQ0JCgteXKObPn++KJAF7DUtysv+jV6dg6wa6MdOmTcO5c+fw2GOPIT8/H/3792/R7tdblBDwR71xS9094fwbC7V2BB2SYrTOAgFoF94O7cLbtdwOTdGACqDz4Jbbp0NL1kwIoUByJByfefUOjhs3Dnv37kVubq7rMXToUEyfPh25ubno0aMHEhIS3EZ7tVqt2LRpU6OjvWZkZNQZIXb9+vWNbmM2mxEbG+v2CKTWdvqYPXs2jh07BovFgp07d2LMmDFaZylAhKN7fd84a1YUEdiDjjOroRSvnDpaDFO4ocn1lixZgu7duyM8PBxDhgzB119/3QK5o4CSKrQ6ujprJmo/AnEZRRH+OQ6FOq9qWGJiYtC/f3+3eVFRUWjfvr1r/gMPPIAnn3wSqampSE1NxZNPPonIyEj86le/cm0zc+ZMdOnSxdVJ2Zw5czBmzBg8/fTTmDx5MtasWYMvvvgC33zzja/lo1DnpxqWlgtY7HkNlRqWsiJ7O7SmqrRDrnfmUCFlSETnQhEQwdJCWMf83tPtn/70J1y8eBGzZ8/GhQsXMHz4cKxfvx4xMdVVvnl5eVCU6gP/yJEjkZ2djYceeggPP/wwevbsiRUrVmD4cP+3qKZQ459fNhab/cQaZgjzOa3GqM6ApdXV6dXPGGaAogjg4AWc+ehHhIXXf0h69m9ZmHHNzfhl8tWQxyQevfp+fLrqIzz/wBP48+i7YWwfAVlRBSU2DG1/0RNKZCDv5CL/aU0X2xtm/6ET/AGL1m1lfA5YNm7c6DYthMCjjz6KRx991ONtAGDq1KmYOnWqr9mhUFT0M3D+CGAMB4xm+9hBRrN92loCqFU+78IZsGw9uRVHCo+4LVOl6qqBUaUKFSqklK75EjVeS+la7pwvpUSYIQxmgxlVF1UAifj5A4GlH34FxSAgDI4O1QwCQrG/FkLUGJ+xOryJjAvDL+YMgtHkfonlQkEZCk9fRGz7cMS0D28wMGhp5ggjLstIQPz3Z1Gx8xSqwupeGrJWVSL30Hf43ZBbUb77NOB4H67ofhm2fZsDZNyJin3nXOtHD+8Mc/e4liwGNZeUoRCvQIjg/gkihD7CLX0ctXRPDx8VNeg/vwFObGt4eac0n3cRZ45DmBKGF3a90OS6AgKKUCCEgAKl+rVQoEABBFyvnZd+Km2VsNgssKpWdO9zKe7t/QASIxKhqhJSlVBtEqrjWTrmSQDOf6QK5P9YhPzDRXjl95tgDHPUYDrSr7LYqvMngP5jkzD6l6kQivaH0eijhagC0PWhEfX2cnvy5EnY/mZD33tHo/PIy1zzu1suxea3dyHhj8MgVQnrTyU4s2QPv65BJTRqWJyXhFRV2msUg5Aecs2AxRMS0MfHRfWqLAf6TwVG/8He70qVxf25fS+fd9Ejrge2T9/uqhlxkpD2gMQZpED41P5ElSpsqq1ZndPZbCr2b8lHlbXurddSSnRMjoFiEPjpwAX87+OjMEcaMXxSj2bn1R8qy60wllairENEk13yN9b1gVAElAgezoJSKLRhEQoEJGxSQuG5pNn4DfdIaDQMC2oRbYB432tSGmNUAv91UYQCxdC8hr0Gg4J+o5vul6JzrzawVtiQuz4P3Qd0QKeUwN5h15gjyw8iXADtrm644azHvTO7vqOsYgkaMjRqWBTHJSGbKmFq+oY4agBvDPcEa1h0jicobw2f1B3R7cKx5vndKDxdrlk+bBerUAWg8+CG+1yq2TtzTRs2bGig6wN+V4NHaHx3pZ/uVgx1DFg8xRoWakWMYQb8Ys4gGEwKvvrXftiqAtuDb4P5iDPDLAQqyxvv2XfevHl4/fXX8eabb+KHH37A3Llz6/bOzH4uglNIHFuDu9EtoI9wi5eEPKKHj4oaF+yHg5YX0y4cY6f3weevf4ePXtyD0Tenol1iFFSbhKGJ9iT+Endpe1R+fxZ7nlyNsDZmhMVHI+mawYju5N7bqle9M/NPIXiESJBpv/AV3GXVw9eKAYtHQuM6K4WeHoM64he/H4QPn9+N7Mf/B6PZAGmTGP+bNPQc3Cmg+87b9yO++vd7SCqJQmrsUFSetsB81oxTe3Ngm30p4rp1dlt/9uzZmD17dkDzRFpo/cdWKe13CYVEZVIAMWDxFP/S6ld+Hsh5A7A11teJtN+tU1EEVBTbny3F1dM2K6AYazwMjocREApqdDjiOLbVnBbA2cNA8oiWKG2r1KV3W9y9+Ar8uPM08n8swrmfS7H+je+RaVLQ7dIOAdmnqqpY+9xzsJSdgKVjGkYvGIGwcDPO7j0K+e4JlPzzMKw3l6KqqhKxKZ0RFd+26TQv2v8GbSWhM3Bk8AvuWgdPSUej22C+MKSHT4oBiydCpCV7sxzaAPz370BMZzT6HhnNQHic4xELxHYGzI5pgwmQNkC12Tt5cz1U+3wpAUj7s1SrXzufEwYAA29pmfK2UqYwA/pkdEafjM6w2VR8/up3WPfKd5g4ewCS0/w/GN721V/CUnYCg665DeN+U91hZIdLu+PEhAuwfV4Ey/v2u4KOygPo//SNTaapllYCAKrOV/g9vxRAIfFjMPhrWPTQbJgBi6eC+S8tkKSjQ7IH9toDDwp6BoOCa+7sj0//+S0+XfotZjwxEpGxng1JUFlZie++2oV2ifFI6pMMg9EAS7kFHzz9T1SUFqLPyMtQeqEEe7/8D8xRSRgzfVKdNJLHDUbF0BIc/Nd/0e6ndohDe5SduYCojo3Xshg7RgAAzBrepk1e0voM2EKcbViC9Syil5ohBiweYrzSAFejOb5BrYnBpOCKW3vjXw9txZHcM+g/pun+XQBg1ZNL8fO+9a7pbumTcPzbLyBtF6EYY7Hl/R0AgKi2vXHjn/8Ak9nsWnfJkiV49tlnkZ+fj379+mHRokWI7WmG7b+F+PnprYi9pQcShvbxb0FJB1r/sUPq5pTffHqILRmweEQPH5VeOd4bRnStTmwHe43Fhfwyj7cpOJyD8NhUpAwYhAPffIhjuz8CoKD/VbMw/q6pOLB1P8yRCnqk93bbrrHRmNtc0gWlrx3B+dUHGbC0OqFybLVfUAmVUdgDhQEL+YY1LK3awKuSsX9bPoZP7uHRgInmqA6wWctw/e9n4frfz4LVYoWltBwx7dsAAPqO6lvvdgsXLsQdd9yBO++8EwCwaNEifP7551i6dCmysrLwc9JuxP3UFvv+ugYi2Yw2fZLQeWx/v5WTNBQCJ/FgvySkFwxYPBEqPwKahTUsrdmlVyZhz39P4EjuGfQZ0bnJ9bv2G4b937yHk4eOITG1G8LMYQgzN97+xWq1YufOnfjLX/7iNn/ChAnYsmULAKDP767F4exNwPdAzLEo2I5dwJHPvkCFoRw2QxWkAoS3jUEkwptfWGp5IdIPi7MVSDAfJvWQdQYs5JuQOeCEppj29gDgzPESjwIWZ5uUyJgYj/dx9uxZ2Gw293GBAMTHx7vGDzIYjOg9fZw9L/t+xMlP90BAgVIoYbKaEC3aAI6hhsqLi2BGnMf7J63p4VQYWNJ1l1DrL2sgMWDxFP/QGsAaltZMUQSS+7ZF8dmLTa576H/fYu+XbwIAyooL0SahvVf7amw05po6pvVEx7SebvMKduxH/o59OL5rJ4YabkXTvbaQPoTGDx5nwBLM9JB7jiXkET18VDrFGpZWr2PXWBzbew5Hcs80uI7logVr//EQACC+52B0uaRng+vW5vFozI1IGNYHydcPxo8le6CE8XdYUAmBHzvsycs/GLCQj/hVbO36jU5E515xWP/696goq6x3nX8/9BQA4LoHsvDrJx/zKn3vR2Oun6raB3BUFB7WgkaI/OCREFBEaJQ1kPhTJBjs/Q9wZr+999faX/A6v06EZ8vVSnu3+lJ17+Yewt4dvifzIIFT34XEL6RQFtshAuNmpeHdh+19sqSNSkSlxYYLBWUoOFKEU0eLcf7n75DQKwN9My5t1j7mzZuHGTNmYOjQocjIyMCrr75adzTmJkhHwCIMhmblgbTS+o8fspUUUev4kgGLJ7Tumv+jOfaxdSLaOsbWcajz11NruqnligmIbG+fL1X37u5rP9c3zxm49JnocxFJ3+I6RqDbgA746l/78dW/9tdZHhYRh2gfGo54NRpzA1Sbvddl1rAEkxCpdXBGLK7jZnDRS5YZsAQDKYEr/gJkcKRa0s61d/XHkdwzOJ9fBktZJXqP6IzodmYUnSlB9kOLENvhMlRaLZA2G4rPnEaHrt28St/X0Zidl4QEA5bgopezYQBJEdwBi14wYPHUvg+BU983sZIERtwL9LwK4EGTWhmDSUHqsLqNYCNjw9D10oHY9dla7PpsrWv+DX96BD2HXNZi+ZPOGhZeEgoeWl9jaCHVxQze8uohzGLA4onemUD5zqbX+2Et8ON/7a8VI2Aw20cpNpoBQ1jjgwM29sWt9LxrdKKWJoTADX98GN9t/AKH/rcFFaUlqLJY8PHzT+HK23+LnkMuQ1SbwN9ozBqWYKWHU2FguW5pFvzb9AUDFk/0vR7o9UDT6xV8Z6+FsVmAKgtgs7o/q5Vo9MvZUFWhMAB9645qS6QXxrAwDJpwHQZNuA4AcDbvGFY8+hdsePVFbACQnHYpuvTtjxE33QyDMTCjekveJRSEgrfGwSvOH6RBfDlID58UAxZ/SuhvfxCFuA5du+HeN7Nx5vhRbHj9ZVRaLdi2ajnMkZEYev2NAdmnqtovCQmFl4SCShCfxD0mVdikAP8yfcOAhYgCpmNKd/zq8ecAAMv+MBtnTxwP2L5YwxKEQqQNC6SECoUBi4/4zSaigCs6fQoVpSX46YfvArYPlY1ug1QI1LBA1cUllWDHgIWIAurUkcN49y9zoKoqrvj1bwK2H8lGt0EoNE7jQkpInm59xktCRBQQFWWl+Oj5p5C3NxexHTvhlgXPIKZ9h4Dtj3cJBalQqGCRKtQGCiqlhE2VUG02+6PK/dlWWQVblQ02mw3S8axW2aBW2edLmw2qTbVP22yQNtWxfRXUKvtrabNVr1tlg6ra03IuU6tskKp9W+mYJx1pSdWGsotWjDpXCpSNBjQcWpQBCxEFxInvvkXe3lwAQEz7jvj8ny84akEkpCohpYSUKmxVVbBVVqKqshK2SiuqrFbYqiphs1bCZquC0RQGg8kExWCAUBQIRYGiKFAU92nLxXIAvCQUTD79v74oPP3/gDnLq0/nwt6zeO3RjcuronGxKhoA0D6ioJ7Rj6UjDemahqxxSzGk+zLUWCbt/1QV2dD3eDaiL54EVEcH4M5OwF3PoslOxGuLA3BMtoft/X6udjsCgOLnGiZ//OVXCQWq6yGgCgVSCMR07ogOP+wG0pL9sJfmYcBCRAHRY8hlGHHTNJz76QSEEICiQMBeAyKEfUwqIQQMRiMMjqDEaAqD0WSCwWSCwRQGxWCwBzNWC6SqQlVVSKlWv1btvwCdr6PbtkdYeITWRScPHc1vj6QOQPuYEke4UTOAqBEHSKCi0oZDP0cjqcMZtIm6WJ2IBCAEqsOAmuOdocalGEdI5FomAAFIaV9fSoH9lg4oiR+IhA4dAIMBwqDYx6ZyPAuDYp+vOMdXq5mHGgWrNW212XC0PAKFMb1q/O0DQiiO7NgDb2FQ7He5ufajQDEaoRgMUBzzFIMBwmCAYnQE7caa8wyOdQ0wmAxQDEYoRgOMRgMUoxEGgwGKSYHRaKrx2giD0QCD0Qij0WDPXy1qWRk2TrwebcK1/THgVcCydOlSLF26FMeOHQMA9OvXD4888ggyMzMBAKdOncKf//xnrF+/HoWFhRgzZgxefPFFpKamNpjmsmXLcPvtt9eZf/HiRYSHh3uTPSLSEYPRiFHTZmidDdK5XhNGot/oLh6tOyGA+VBtKvbfuxERGVcifs5kv6ef4PcUW5AziFG1bXPk1cXepKQkPPXUU8jJyUFOTg6uuuoqTJ48Gd9//z2klLjhhhtw5MgRrFmzBrt370ZKSgquvvpqlJU13lNrbGws8vPz3R4MVoiIWrnQaHMb/ETNqiTteFXDMmmSe2+rTzzxBJYuXYpt27bBZDJh27Zt+O6779CvXz8AwJIlS9CpUycsX74cd955Z4PpCiGQkBDU8ScRETVDfZcgtOA6FesjO/pSc/BGDTW7Ob3NZkN2djbKysqQkZEBi8UCAG41IwaDAWFhYfjmm28aTau0tBQpKSlISkrC9ddfj927dze5f4vFguLiYrcHERER+ZnzzrtgC1j27t2L6OhomM1m3HPPPVi9ejXS0tLQp08fpKSkYP78+bhw4QKsViueeuopFBQUID8/v8H0+vTpg2XLlmHt2rVYvnw5wsPDMWrUKBw6dKjRfGRlZSEuLs71SE7WruUyEREFN6k6m+2yiqU21wWhYAtYevfujdzcXGzbtg2/+93vMGvWLOzbtw8mkwmrVq3CwYMH0a5dO0RGRmLjxo3IzMyEoZHbDEeMGIFf//rXGDhwIEaPHo33338fl1xyCV588cVG8zF//nwUFRW5HidOnPC2KEREpBHXyU9v8YHe8qMHOml06/VtzWFhYejVqxcAYOjQodixYwdeeOEFvPLKKxgyZAhyc3NRVFQEq9WKjh07Yvjw4Rg6dKjH6SuKgmHDhjVZw2I2m2E2m73NPhERUV2u2gNGLHUEexsWJymlq/2KU1xcHDp27IhDhw4hJycHkyd7fouYlBK5ubno3Lmzr1kjIiLyjPOSEOOVuly9RwdRDcuDDz6IzMxMJCcno6SkBNnZ2di4cSPWrVsHAFi5ciU6duyIrl27Yu/evZgzZw5uuOEGTJhQfff8zJkz0aVLF2RlZQEAFixYgBEjRiA1NRXFxcVYvHgxcnNz8fLLL/uxmEREpCu8pTl46KSGxauA5dSpU5gxYwby8/MRFxeHAQMGYN26dRg/fjwAID8/H/PmzcOpU6fQuXNnzJw5Ew8//LBbGnl5eW7DvxcWFuLuu+9GQUEB4uLikJ6ejs2bN+Oyyy7zQ/GIiEjP9FKjIXlJqEHOW8+1bnTrVcDyxhtvNLr8/vvvx/3339/oOhs3bnSbfv755/H88897kw0iIgpyuq1gYbzSsGDq6ZaIiKhV0rj2wGnz5s2YNGkSEhMTIYTAhx9+qHWW7ITQ/D1iwEJERC1Pb5dgdBKwlJWVYeDAgXjppZe0zoo7UWNwSo1wtGYiIiKd9AuTmZnpGlBYV1jDQkREoUwvjW6pCUJo3uiWAQsREbU4fVyAqaY6nvUyGKPeCICNbomIKITpJT7QSRsW3RLQ/D1iwEJERC1Pb/GBqw2wXiIonREKAxYiIgpdugkPpHO0ZqqXALSOMnmXEBERkZPGEUtpaSkOHz7smj569Chyc3PRrl07dO3aVcOcaX+XEAMWIiJqebq7JKSPDOXk5ODKK690Tc+bNw8AMGvWLCxbtkyjXDmasGjc6JYBCxERaUd3bUa0zc/YsWM1v324PlJhGxYiIgpBUmdVLFrXHuge7xIiIiLSD/bD0hDtu+ZnwEJERC1PbxUaOumaX7fYNT8REYUyvVRo6LHdiJ7oodEtAxYiIiIHvQRQuqOwhoWIiEKQ3uozWMPSFAYsREQUyvRWo8EqlvoJNrolIqJQpLcKDdawNI63NRMRUSgTuqtiofoICEhV1TQPDFiIiIhYw9I4ITSvFWPAQkRE5MIan3qxHxYiIiIdcPQxwp5uG8A2LEREFIr0dhtxVXGJ1lnQOd4lREREIejHXWcAAMYwfZyGNs39JwDAGGnSOCf6JAQb3RIRUQiyVdlPfimXdtA4J3ZKlxRAqki9cZTWWdEn7StYGLAQEVHLU20SBqMCRdFHmxElNg4xVedgMLOGpX5sdEtERCFItakQBs+Dlc2bN2PSpElITEyEEAIffvhh4DJHdfEuISIioqaVlZVh4MCBeOmll7TOSmjSQdf8Rk33TkREIUl4+Ys9MzMTmZmZAcwRNUpA80a3DFiIiKjlaX+FoVWQUkKtqIC1tBSVpSWoLC2DWnERVeXlUK0W2KpsUFUb1KpKqDYbzp4+hYqL5YhPSASkhFRV+y3m0v4sVWn/YFzLVEhV4qxahW6VlZqW1auAZenSpVi6dCmOHTsGAOjXrx8eeeQRV9R76tQp/PnPf8b69etRWFiIMWPG4MUXX0Rqamqj6a5atQoPP/wwfvzxR/Ts2RNPPPEEbrzxxuaViIiIdE8HVxjcWCqLUFp+CB/d87n9BK+q1Q+pQlWlo+8Y6fi/Rual/R/XHCndi1Z7OeyBhgLADAEVgAoJ1ZGuc1pKQBX2Pu3s09K+niNJVQAqBGQLNFyuiolFTMl5dA34nhrmVcCSlJSEp556Cr169QIAvP3225g8eTJ2796NtLQ03HDDDTCZTFizZg1iY2OxcOFCXH311di3bx+ioqLqTXPr1q2YNm0aHn/8cdx4441YvXo1br75ZnzzzTcYPny47yUkIiIdErVO4doqlvm4qB5GwXkJBQKKcH8IIewDNQoBCEARjiagwtmZvyNocPSUW91hrmN4xxo96Dp707VJCYtqc+3DJBTXvgxCgRACiiKgCAWKwQCD0QjFaILBaIIhzATFaIQhzAxjWBhM4REwhofDGB4Og/NhMkMxGWAwmqAYDFCMRlRarZCQiIyNgxAGCEVAKApgMEBAQBgUQAgIgwEQAoqiAELBW/94Aqa+fQL/QTTCq4Bl0qRJbtNPPPEEli5dim3btsFkMmHbtm347rvv0K9fPwDAkiVL0KlTJyxfvhx33nlnvWkuWrQI48ePx/z58wEA8+fPx6ZNm7Bo0SIsX768OWUiIiKd01sNixIbA2NRW9z1zttaZ0WXFMWgdRaaf5eQzWZDdnY2ysrKkJGRAYvFAgAIDw93rWMwGBAWFoZvvvmmwXS2bt2KCRMmuM275pprsGXLlkb3b7FYUFxc7PYgIqLgoIO7ZN1JgAMfNkb7CNPrgGXv3r2Ijo6G2WzGPffcg9WrVyMtLQ19+vRBSkoK5s+fjwsXLsBqteKpp55CQUEB8vPzG0yvoKAA8fHxbvPi4+NRUFDQaD6ysrIQFxfneiQnJ3tbFCIi0oqXEUtpaSlyc3ORm5sLADh69Chyc3ORl5fnpwzpKXrSJ60DTK8Dlt69eyM3Nxfbtm3D7373O8yaNQv79u2DyWTCqlWrcPDgQbRr1w6RkZHYuHEjMjMzYTA0XpVUe3RMKWWTI2bOnz8fRUVFrseJEye8LQoREWlECO9ChJycHKSnpyM9PR0AMG/ePKSnp+ORRx4JTAbJnQ5Gsfb6tuawsDBXo9uhQ4dix44deOGFF/DKK69gyJAhyM3NRVFREaxWKzp27Ijhw4dj6NChDaaXkJBQpzbl9OnTdWpdajObzTCbzd5mn4iI9MKLiGXs2LEBHeHZnrb2J2VdC/aebqWUrvYrTnFxcejYsSMOHTqEnJwcTJ48ucHtMzIysGHDBrd569evx8iRI33NGhER6ZSzFj2QQQj5l9Z3dXlVw/Lggw8iMzMTycnJKCkpQXZ2NjZu3Ih169YBAFauXImOHTuia9eu2Lt3L+bMmYMbbrjBrVHtzJkz0aVLF2RlZQEA5syZgzFjxuDpp5/G5MmTsWbNGnzxxReNNtQlIqIg56zM0EvFhpS6uOyhV3p4a7yqYTl16hRmzJiB3r17Y9y4cdi+fTvWrVuH8ePHAwDy8/MxY8YM9OnTB/fffz9mzJhR59bkvLw8t0a4I0eORHZ2Nt566y0MGDAAy5Ytw4oVK9gHCxFRK+Y8AeqlfkUvcZNuB3n0ttFRAHhVw/LGG280uvz+++/H/fff3+g6GzdurDNv6tSpmDp1qjdZaVGssiQi8real4T0ECroIx/OQR5vv/12TJkyRevsuNH6XMixhDzQ1B1LRETkHVHzkpAe6OSHqV4HedTDWdDnRrdERETecl0S0kmgoI9c6FkQdhxHRETkK6E4LwlpnBEXNrptitafFS8JERFRo04euoALBeX2gfKEgH08PFFjWkDUmKcIx7RjoED3OMA+UXiqHAAgVZ1ELDrJhm7pIJhjwEJERI1a9+p3uFhS6fd0DUYFikH7EyEAR/WBTvKiQwKAVFVN88CAhYiIGiUUgWHXd8ewid0gVQmpAqqUjteOaVVCOuapqgQkHNPuadVss2KONMFo0n4UYDvJcKVJvEuIiIh0TFGEa4w3YRCAAdBLmOEv9sGatQ9ZSktLcfjwYde0c5DHdu3aoWvXrtplTPu3hgELERE1QeiorUmg6KR4OTk5uPLKK13T8+bNAwDMmjULy5Yt0yhXgIDQ/I4uBiwe0PpDIiLSkqKIVh+wSJ10HBfoQR59onG2eFuzB9hxHBGFMsWgQLXp9CRKIYMBCxERNUoxiNYfsHDww0YJAajsOI6IiPRMMQj7nT+tmeRdQk3S+FIVAxYiImqUooRADQsAPbRh0S0d1D4xYCEiokaFQg2LhGS80gj7XULa5oEBCxERNUooAqpN215OA87eEYvWudA5XhIiIiIdUwwKZKu/JNTay+c7rd8hBixERNSoULhLSIJdWDRKgI1uiYhI30KhDYvWJ+NgoPU7xICFiIgaVXKuArYqrU9XgSNViaLTh5teMYQJCM0jFgYsRETUqIiYMFjKK7XORsCczjsPaSvRw527+iWE5rVQDFiIiKhRUpWI6xihdTYCptJiBQAMm3yjxjmhxjBgISKiRklVQlFab/WDrdJee2QwcDzghtgrWFjDQkREOqaqEsLQigOWKkfAYjJpnBM9EwxYiIhI31Rba69hqQLAgKUxevj0Wf9FRESNUlv5JaGqKnsbFoPRBCklbFVVsFkrUVVhga3CCpulEqqqQtgAWFXABihRRsdZ3P673/5SgVAEhCIAISAEIBQFQiiAAsd8xzpCAIr9IYSwJ6BKSGEfIkBKAMJeoyFVCSklpM0GqABU1TEPkDbVvp1U7Z37qfaHVCUgnc+wL5eA61Yf4frH3tjY0eJYQLga2Eo40pCAsdIISG3/BhiwEBFR4yTsJ9fWqqwK1yffg7A155G3diMUGNiJXC39xHCopRWa5oEBCxERNaH19sECADGRnQBjKQo7lsHY1gglDFCMChSTEUqYEYrR4KgNAVBsg7RIoL0Cx5CJrmepSgDSXgsi7bUiUOGqqYBjOCb7fMc86ehl11nb4RjTSNS8CCMEhGJ/hrDnw1Uro9if7TU5cC13reeqwREQ0rGNsGfT+bHa26ZIVw2MlNIRsAlHxYsAvixCfHLPAH0CnmHAQkREjZKtfCBjIQQkgIQJQ9Dh0o5aZ0eXCr8rgsFg0DQPbHRLREShzdmsg5eBmsC7hIiIiDTjuluX8UqjtL4wyICFiIgIcG83Qm708N54FbAsXboUAwYMQGxsLGJjY5GRkYHPPvvMtby0tBT33XcfkpKSEBERgb59+2Lp0qWNprls2TIIIeo8Kiq0bY1MREShwdkhWqCvCG3evBmTJk1CYmIihBD48MMPA7tDf9O4isWrRrdJSUl46qmn0KtXLwDA22+/jcmTJ2P37t3o168f5s6di6+++grvvvsuunXrhvXr12P27NlITEzE5MmTG0w3NjYWBw4ccJsXHh7ejOIQEZG/CQGcOVGCPV+eqGeh+3q1Z9YXBLjm1bPQOattQhQSU9vUWV54uBD5G47b1611Kcdx042r7xAAjj5KnAsdK7ieAWFToZRXIaZuNv2urKwMAwcOxO23344pU6a0wB79SFTfE6UVrwKWSZMmuU0/8cQTWLp0KbZt24Z+/fph69atmDVrFsaOHQsAuPvuu/HKK68gJyen0YBFCIGEhATvc09ERAHXPikaR3PP4uyJ0upTljMiqHEOk3Ve1DjJyfqWuadVe3tFERAGAcUgoCj255RKGy4xK7A0cImiRn9o7mmKmlkQrnVUAVQJgfNRJiSkxNabpr9kZmYiMzMzoPsIFPtN3Npq9m3NNpsNK1euRFlZGTIyMgAAl19+OdauXYvf/OY3SExMxMaNG3Hw4EG88MILjaZVWlqKlJQU2Gw2DBo0CI8//jjS09Mb3cZiscBisbimi4uLm1sUIiJqxPjb+7Xo/ipKK3FkzxmoVSpUVUK1VT+ijhQChRXo9dCIFs1TyNPBHVReByx79+5FRkYGKioqEB0djdWrVyMtLQ0AsHjxYtx1111ISkqC0WiEoih4/fXXcfnllzeYXp8+fbBs2TJceumlKC4uxgsvvIBRo0Zhz549SE1NbXC7rKwsLFiwwNvsExGRzoVHm5A2KrHeZYWfHkXFvqoWzhHpgdcBS+/evZGbm4vCwkKsWrUKs2bNwqZNm5CWlobFixdj27ZtWLt2LVJSUrB582bMnj0bnTt3xtVXX11veiNGjMCIEdWR8qhRozB48GC8+OKLWLx4cYP5mD9/PubNm+eaLi4uRnJysrfFISKiYKK28l7sdCyo2rAAQFhYmKvR7dChQ7Fjxw688MILWLRoER588EGsXr0aEydOBAAMGDAAubm5eO655xoMWGpTFAXDhg3DoUOHGl3PbDbDbDZ7m30iIgpmUuri8kSo0cM77nM/LFJKWCwWVFZWorKyEorinqTBYICqql6ll5ubi86dO/uaNSIiam0k7OPqUAsT1XdeacSrGpYHH3wQmZmZSE5ORklJCbKzs7Fx40asW7cOsbGxuOKKK/DHP/4RERERSElJwaZNm/DOO+9g4cKFrjRmzpyJLl26ICsrCwCwYMECjBgxAqmpqSguLsbixYuRm5uLl19+2b8lJSKioCeDuIaltLQUhw8fdk0fPXoUubm5aNeuHbp27aphzpqmh3fcq4Dl1KlTmDFjBvLz8xEXF4cBAwZg3bp1GD9+PAAgOzsb8+fPx/Tp03H+/HmkpKTgiSeewD333ONKIy8vz60WprCwEHfffTcKCgoQFxeH9PR0bN68GZdddpmfikhERK2GKu0jFAehnJwcXHnlla5pZzvMWbNmYdmyZRrlygsaV7EIKbWu5PGP4uJixMXFoaioCLGx/r2X/vDhw652O0REpJ0LHxyC9WQp4u9rvOsL8q/9L3+NiJgopMwc7Pe0PT1/80ogEREFDalKjqqsCaH5XUIMWIiIKHhIBO0loWCmh3ecAQsREQUPyX5YQhUDFiIiCh5q8N4lFNSE9mMJMWAhIqKgEcR3NQc1AaH5XUIMWIiIKHhIiapzF7XORegRbHRLRETkMfViFWxFVqhWm9ZZCSkC0PyaEAMWIiIKGlFDE+wvVK1bVIQYHVyGY8BCRETBg2ct7bCGhYiIiPRNQErPBzIOBAYsRERE1Cg99C7s1eCHoaqVDLdEREQ6JKWsvtwiHf+4TdtfyKbWcazgdsqqOeE23z0N6f6P/anmplUSMGobtDBgISKioHNq0S6IMAPcTtyA28lb1ppu6IQta03Xt44ziTon9YbWa2IdrduDeKtKXERY3zaa5oEBCxERBQ1zjzaIHtMFqKrRRb/zcoVr2vGPqH5ZPYFa6wq3JNx6pRN1txUNpiXc9i+ayFf1ek2v48pjU+s5XojG8lYrTdReXDvPjtfG0mKI9mZoiQELEREFDUOUCW2u66F1NkKO+QJQVVWlaR7Y6NYDemhsREREpBU9nAcZsHiIDW+JiCiUaX0eZMDigaioKJSVlWmdDSIiIk2whiVIxMXFoaioSOtsEBERhSwGLB6IiIjAxYscHZSIiEIXLwkFAT1UhREREWlFD+dBBiwe0jqyJCIi0pLW50EGLERERNQo1rAQEREReYABi4f0EF0SERFphZeEiIiISNf08KOdAQsRERE1iTUsREREpGusYSEiIiLyAAMWIiIiahIvCREREZGuBd0loaVLl2LAgAGIjY1FbGwsMjIy8Nlnn7mWl5aW4r777kNSUhIiIiLQt29fLF26tMl0V61ahbS0NJjNZqSlpWH16tXelyTAtI4siYiItKT1edCrgCUpKQlPPfUUcnJykJOTg6uuugqTJ0/G999/DwCYO3cu1q1bh3fffRc//PAD5s6di9///vdYs2ZNg2lu3boV06ZNw4wZM7Bnzx7MmDEDN998M7Zv3+5byYiIiMgv9FDDIqSPIVO7du3w7LPP4o477kD//v0xbdo0PPzww67lQ4YMwXXXXYfHH3+83u2nTZuG4uJit5qaa6+9Fm3btsXy5cs9zkdxcTHi4uJQVFSE2NjY5heoAYcOHUJqaqrf0yUiItK7ixcv4ty5c0hKSvJ72p6ev5vdhsVmsyE7OxtlZWXIyMgAAFx++eVYu3Ytfv75Z0gp8dVXX+HgwYO45pprGkxn69atmDBhgtu8a665Blu2bGl0/xaLBcXFxW4PIiIiCgytLwkZvd1g7969yMjIQEVFBaKjo7F69WqkpaUBABYvXoy77roLSUlJMBqNUBQFr7/+Oi6//PIG0ysoKEB8fLzbvPj4eBQUFDSaj6ysLCxYsMDb7BMREZGX9HBJyOsalt69eyM3Nxfbtm3D7373O8yaNQv79u0DYA9Ytm3bhrVr12Lnzp34xz/+gdmzZ+OLL75oNM3ab4SUssk3Z/78+SgqKnI9Tpw44W1RvKKHD4uIiEgrQVfDEhYWhl69egEAhg4dih07duCFF17AokWL8OCDD2L16tWYOHEiAGDAgAHIzc3Fc889h6uvvrre9BISEurUppw+fbpOrUttZrMZZrPZ2+wTERGRl/Two93nfliklLBYLKisrERlZSUUxT1Jg8EAVVUb3D4jIwMbNmxwm7d+/XqMHDnS16wRERFRK+FVDcuDDz6IzMxMJCcno6SkBNnZ2di4cSPWrVuH2NhYXHHFFfjjH/+IiIgIpKSkYNOmTXjnnXewcOFCVxozZ85Ely5dkJWVBQCYM2cOxowZg6effhqTJ0/GmjVr8MUXX+Cbb77xb0mJiIio2YLqktCpU6cwY8YM5OfnIy4uDgMGDMC6deswfvx4AEB2djbmz5+P6dOn4/z580hJScETTzyBe+65x5VGXl6eWy3MyJEjkZ2djYceeggPP/wwevbsiRUrVmD48OF+KiIRERH5Qg+XhHzuh0UvAt0Py+HDh11td4iIiEKJ1WrFyZMn0a1bN7+nHfB+WIiIiCg06KGGhQELERER6R4DFiIiImqS1i1IGLAQERFRo3hJiIiIiIICa1iIiIhI11jDQkREROQBBixERETUJF4SIiIiIl3jJSEiIiIKCqxhISIiIl1jDQsRERGRBxiwEBERUaNYw0JERETkAQYsREREpHsMWIiIiEj3GLAQERFRk3hbMxEREVETGLAQERGR7jFgISIiIt1jwEJERES6x4CFiIiIdI8BCxEREekeAxYiIiLSPQYsREREpHsMWIiIiEj3GLAQERGR7jFgISIiIt1jwEJERES6x4CFiIiIdI8BCxEREemeVwHL0qVLMWDAAMTGxiI2NhYZGRn47LPPXMuFEPU+nn322QbTXLZsWb3bVFRUNL9URERE1KoYvVk5KSkJTz31FHr16gUAePvttzF58mTs3r0b/fr1Q35+vtv6n332Ge644w5MmTKl0XRjY2Nx4MABt3nh4eHeZI2IiIhaMa8ClkmTJrlNP/HEE1i6dCm2bduGfv36ISEhwW35mjVrcOWVV6JHjx6NpiuEqLMtERERkVOz27DYbDZkZ2ejrKwMGRkZdZafOnUKn3zyCe64444m0yotLUVKSgqSkpJw/fXXY/fu3U1uY7FYUFxc7PYgIiKi1snrgGXv3r2Ijo6G2WzGPffcg9WrVyMtLa3Oem+//TZiYmJw0003NZpenz59sGzZMqxduxbLly9HeHg4Ro0ahUOHDjW6XVZWFuLi4lyP5ORkb4tCREREHhJCaLt/KaX0ZgOr1Yq8vDwUFhZi1apVeP3117Fp06Y6QUufPn0wfvx4vPjii15lSFVVDB48GGPGjMHixYsbXM9iscBisbimi4uLkZycjKKiIsTGxnq1T08cPnzY1XaHiIgo1ATqPFhcXIy4uLgmz99etWEBgLCwMFeGhw4dih07duCFF17AK6+84lrn66+/xoEDB7BixQqvM64oCoYNG9ZkDYvZbIbZbPY6fSIiIgo+PvfDIqV0q+kAgDfeeANDhgzBwIEDm5Vebm4uOnfu7GvWiIiIqJXwqoblwQcfRGZmJpKTk1FSUoLs7Gxs3LgR69atc61TXFyMlStX4h//+Ee9acycORNdunRBVlYWAGDBggUYMWIEUlNTUVxcjMWLFyM3Nxcvv/yyD8UiIiKi1sSrgOXUqVOYMWMG8vPzERcXhwEDBmDdunUYP368a53s7GxIKXHrrbfWm0ZeXh4Upbpip7CwEHfffTcKCgoQFxeH9PR0bN68GZdddlkzi0REREStjdeNbvXK00Y7zcVGt0REFMq0bnTLsYSIiIhI9xiwEBERke4xYCEiIiLdY8BCREREuseAhYiIiHSPAQsRERHpHgMWIiIi0j0GLERERKR7DFiIiIhI9xiwEBERke4xYCEiIiLdY8BCREREuseAhYiIiHSPAQsRERHpHgMWIiIi0j0GLERERKR7DFiIiIhI9xiwEBERke4xYCEiIiLdY8BCREREuseAhYiIiHSPAQsRERHpHgMWIiIi0j0GLERERKR7DFiIiIhI9xiwEBERke4xYCEiIiLdY8BCREREuseAhYiIiHSPAQsRERHpHgMWIiIi0j2vApalS5diwIABiI2NRWxsLDIyMvDZZ5+5lgsh6n08++yzjaa7atUqpKWlwWw2Iy0tDatXr25eaYiIiKhV8ipgSUpKwlNPPYWcnBzk5OTgqquuwuTJk/H9998DAPLz890eb775JoQQmDJlSoNpbt26FdOmTcOMGTOwZ88ezJgxAzfffDO2b9/uW8mIiIio1RBSSulLAu3atcOzzz6LO+64o86yG264ASUlJfjyyy8b3H7atGkoLi52q6m59tpr0bZtWyxfvtzjfBQXFyMuLg5FRUWIjY31rhAeOHz4MHr16uX3dImIiIJBoM6Dnp6/jc3dgc1mw8qVK1FWVoaMjIw6y0+dOoVPPvkEb7/9dqPpbN26FXPnznWbd80112DRokWNbmexWGCxWFzTxcXFnme+Gc6fP4+8vLwm1/Mm/gvUur5s449tA7G9EKLB5bWXNbXc023rW+bJ8piYGMTHx9e7jKg1kVI2+nCuU3NdLeb5kkZ933MhBCIjIwEAqqpCSlnnuea6zmej0Yjw8HCYzWaYzWaYTKYGjyNUl9cBy969e5GRkYGKigpER0dj9erVSEtLq7Pe22+/jZiYGNx0002NpldQUFDn4B4fH4+CgoJGt8vKysKCBQu8zX6zDRo0yOuTcHP+EL3dxpc/9uZuG6h9tpYv7qlTp3D48GGts0E+cJ6o6vvOt5a/U39pqO2ic1nNdXyZV3uZp9v6sv+GPmubzYby8nLXOoqiuJ6dr4G6QVNlZSUsFgvKyspw7tw5VFVVNRgUaamhc13btm1bOCfuvA5YevfujdzcXBQWFmLVqlWYNWsWNm3aVCdoefPNNzF9+nSEh4c3mWZ9v4Cb+gDnz5+PefPmuaaLi4uRnJzsRUm8ExYWFrC0qXWJj49nDQtRK2YwGBATE+P1diaTyVUzQ97zOmAJCwtzXcMaOnQoduzYgRdeeAGvvPKKa52vv/4aBw4cwIoVK5pMLyEhoU5tyunTp5s84Dur1IiIiKj187kfFimlW1sSAHjjjTcwZMgQDBw4sMntMzIysGHDBrd569evx8iRI33NGhEREbUSXtWwPPjgg8jMzERycjJKSkqQnZ2NjRs3Yt26da51iouLsXLlSvzjH/+oN42ZM2eiS5cuyMrKAgDMmTMHY8aMwdNPP43JkydjzZo1+OKLL/DNN9/4UCwiIiJqTbwKWE6dOoUZM2YgPz8fcXFxGDBgANatW4fx48e71snOzoaUErfeemu9aeTl5UFRqit2Ro4ciezsbDz00EN4+OGH0bNnT6xYsQLDhw9vZpGIiIiotfG5Hxa9CHQ/LEREROR/np6/OZYQERER6R4DFiIiItI9BixERESkewxYiIiISPcYsBAREZHuMWAhIiIi3WPAQkRERLrHgIWIiIh0jwELERER6Z7XozXrlbPD3uLiYo1zQkRERJ5ynreb6ni/1QQsJSUlAIDk5GSNc0JERETeKikpQVxcXIPLW81YQqqq4uTJk4iJiYEQImD7KS4uRnJyMk6cOBGSYxaFevkBvgcsP8sfyuUH+B74u/xSSpSUlCAxMdFtcOTaWk0Ni6IoSEpKarH9xcbGhuQfqlOolx/ge8Dys/yhXH6A74E/y99YzYoTG90SERGR7jFgISIiIt1jwOIls9mMv/3tbzCbzVpnRROhXn6A7wHLz/KHcvkBvgdalb/VNLolIiKi1os1LERERKR7DFiIiIhI9xiwEBERke4xYCEiIiLdY8DSiCeeeAIjR45EZGQk2rRpU+86eXl5mDRpEqKiotChQwfcf//9sFqtbuu8//77GDRoECIjI5GSkoJnn322BXLvO3+V//PPP8eIESMQExODjh07YsqUKTh69GgLlMA3/ij/o48+CiFEnUdUVFQLlaL5/PX5Synx3HPP4ZJLLoHZbEZycjKefPLJFiiBb/xR/mPHjtX7+a9bt66FSuEbf/0NOB0+fBgxMTENpqU3/ij/gQMHcOWVVyI+Ph7h4eHo0aMHHnroIVRWVrZQKZrPH+XfuHEjJk+ejM6dOyMqKgqDBg3Ce++916z8tJqebgPBarXil7/8JTIyMvDGG2/UWW6z2TBx4kR07NgR33zzDc6dO4dZs2ZBSokXX3wRAPDZZ59h+vTpePHFFzFhwgT88MMPuPPOOxEREYH77ruvpYvkFX+U/8iRI5g8eTLmzZuH9957D0VFRZg7dy5uuukm7N69u6WL5BV/lP///b//h3vuucdtu3HjxmHYsGEtUgZf+KP8ADBnzhysX78ezz33HC699FIUFRXh7NmzLVmUZvFX+QHgiy++QL9+/VzT7dq1C3j+/cGf70FlZSVuvfVWjB49Glu2bGmpIvjEH+U3mUyYOXMmBg8ejDZt2mDPnj246667oKqq7gN3f5R/y5YtGDBgAP785z8jPj4en3zyCWbOnInY2FhMmjTJuwxJatJbb70l4+Li6sz/9NNPpaIo8ueff3bNW758uTSbzbKoqEhKKeWtt94qp06d6rbd888/L5OSkqSqqgHNt7/4Uv6VK1dKo9EobTaba521a9dKIYS0Wq0Bz7s/+FL+2nJzcyUAuXnz5kBl1+98Kf++ffuk0WiU+/fvb6ns+p0v5T969KgEIHfv3t1CuQ0Mf3wH/vSnP8lf//rXDaalZ/48Bkgp5dy5c+Xll18eiKwGhL/Lf91118nbb7/d63zwkpAPtm7div79+yMxMdE175prroHFYsHOnTsBABaLBeHh4W7bRURE4KeffsLx48dbNL/+5kn5hw4dCoPBgLfeegs2mw1FRUX417/+hQkTJsBkMmmVdb/wpPy1vf7667jkkkswevTolspmwHhS/o8++gg9evTAxx9/jO7du6Nbt2648847cf78ea2y7TfefP6/+MUv0KlTJ4waNQr/+c9/WjqrAePpe/Df//4XK1euxMsvv6xFNgOmOceAw4cPY926dbjiiitaKpsB05zyA0BRUVGzahkZsPigoKAA8fHxbvPatm2LsLAwFBQUALB/eB988AG+/PJLqKqKgwcPYtGiRQCA/Pz8ls6yX3lS/m7dumH9+vV48MEHYTab0aZNG/z000/Izs7WIst+5Un5a7JYLHjvvfdwxx13tFQWA8qT8h85cgTHjx/HypUr8c4772DZsmXYuXMnpk6dqkWW/cqT8kdHR2PhwoX4z3/+g08//RTjxo3DtGnT8O6772qRZb/z5D04d+4cbrvtNixbtqzVDRTozTFg5MiRCA8PR2pqKkaPHo3HHnusJbMaEN4eAwHgP//5D3bs2IHbb7/d6/2FXMDSUCPImo+cnByP0xNC1JknpXTNv+uuu3Dffffh+uuvR1hYGEaMGIFbbrkFAGAwGPxTKC+0dPkLCgpw5513YtasWdixYwc2bdqEsLAwTJ06FVKDTpZbuvw1ffDBBygpKcHMmTN9KoMvWrr8qqrCYrHgnXfewejRozF27Fi88cYb+Oqrr3DgwAG/lctTLV3+Dh06YO7cubjsssswdOhQPPbYY5g9ezaeeeYZv5XJW1ocA3/1q19hzJgxfiuDL7Q6BqxYsQK7du3Cv//9b3zyySd47rnnfC5Lc2h5DNy4cSNuu+02vPbaa25tujwVco1u77vvPlfA0JBu3bp5lFZCQgK2b9/uNu/ChQuorKx0RZ1CCDz99NN48sknUVBQgI4dO+LLL7/0aj/+1NLlf/nllxEbG+t2gH733XeRnJyM7du3Y8SIEd4VwEctXf6aXn/9dVx//fVISEjwOL/+1tLl79y5M4xGIy655BLXOn379gVgv7ugd+/eXuTed1p+/k4jRozA66+/7tE+AqGl34P//ve/WLt2resELaWEqqowGo149dVX8Zvf/Mb7QvhAq7+B5ORkAEBaWhpsNhvuvvtu/OEPf2jxH65alX/Tpk2YNGkSFi5c2OwfbSEXsHTo0AEdOnTwS1oZGRl44oknkJ+fj86dOwMA1q9fD7PZjCFDhritazAY0KVLFwDA8uXLkZGRgU6dOvklH95o6fKXl5fX+UI6p1VV9Us+vKHV53/06FF89dVXWLt2rV/23VwtXf5Ro0ahqqoKP/74I3r27AkAOHjwIAAgJSXFL/nwhlaff027d+92ra+Fln4Ptm7dCpvN5tpmzZo1ePrpp7FlyxbXMbEl6eFvQEqJyspKTWqZtSj/xo0bcf311+Ppp5/G3Xff3fwdet1MN4QcP35c7t69Wy5YsEBGR0fL3bt3y927d8uSkhIppZRVVVWyf//+cty4cXLXrl3yiy++kElJSfK+++5zpXHmzBm5dOlS+cMPP8jdu3fL+++/X4aHh8vt27drVSyP+aP8X375pRRCyAULFsiDBw/KnTt3ymuuuUampKTI8vJyrYrmEX+U3+mhhx6SiYmJsqqqqqWL0Wz+KL/NZpODBw+WY8aMkbt27ZI5OTly+PDhcvz48VoVy2P+KP+yZcvke++9J/ft2yf3798vn332WWkymeTChQu1KpZX/PkdcAqmu4T8Uf53331XrlixQu7bt0/++OOP8v3335ddunSR06dP16pYHvNH+b/66isZGRkp58+fL/Pz812Pc+fOeZ0fBiyNmDVrlgRQ5/HVV1+51jl+/LicOHGijIiIkO3atZP33XefrKiocC0/c+aMHDFihIyKipKRkZFy3Lhxctu2bRqUxnv+KL+U9tvc0tPTZVRUlOzYsaP8xS9+IX/44YcWLo33/FV+m80mk5KS5IMPPtjCJfCNv8r/888/y5tuuklGR0fL+Ph4edtttzXrYNXS/FH+ZcuWyb59+8rIyEgZExMjhwwZIv/1r39pUJrm8dffQE3BFLD4o/zZ2dly8ODBMjo6WkZFRcm0tDT55JNPyosXL2pQIu/4o/wNpXHFFVd4nR8hpQZ1UkREREReCLm7hIiIiCj4MGAhIiIi3WPAQkRERLrHgIWIiIh0jwELERER6R4DFiIiItI9BixERESkewxYiIiISPcYsBAREZHuMWAhIiIi3WPAQkRERLrHgIWIiIh07/8DuR8YQcB7yd4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below I plot these again by county no, with faded neighboring counties\n",
      "0   [41, 52, 54, 29, 25, 10, 24]\n",
      "1   [58, 48, 38, 63, 61, 44, 32, 37, 9, 31]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are 721714.25 90214\n",
      "let's decide whether to delete, accept, or modify list [41, 52, 54, 29, 25, 10, 24] with pop 76951.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [41, 52, 54]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [41, 52, 54, 29, 25, 10, 24] with [41, 52, 54]\n",
      "let's decide whether to delete, accept, or modify list [58, 48, 38, 63, 61, 44, 32, 37, 9, 31] with pop 88334.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [58, 48, 38, 61, 63, 32, 9, 31, 50]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [58, 48, 38, 63, 61, 44, 32, 37, 9, 31] with [58, 48, 38, 61, 63, 32, 9, 31, 50]\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [42, 17, 57, 56, 34, 3]\n",
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [4, 36, 45, 5]\n",
      "enter 1 if you want to manually add another corner-county cluster 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our final pops and fused-county lists are...\n",
      "44650.0 [41, 52, 54]\n",
      "65547.0 [58, 48, 38, 61, 63, 32, 9, 31, 50]\n",
      "105949.0 [42, 17, 57, 56, 34, 3]\n",
      "42401.0 [4, 36, 45, 5]\n"
     ]
    },
    {
     "data": {
      "image/png": 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BYfg6jrNpwvnV8a8Ab8NbIURN/oTFcMRBwtJq6vEjRxKWIKhWdE0oMTGRwYMHs3LlyhrTV65cyYgRIyyKKnKqLgnZs9Ftr7a9ANh5YqfFkQhhP6bbjcPpbJW1vyJ08ZC2ilpmz57N9OnTGTJkCMOHD+fZZ59l79693HTTTVaHFnaBRrc2vK1Za81PV/wUgKlnTLU4GiHsx+N2x0ntCpw4XIqn0p6Xru0iPj4JLeQxNQ6j9WT406ZN4+jRo9x3333k5+fTv39/3nnnHbp1a32jBPt/mZk2rGE5WXmSzQc3c0GXC5h8eutsJCdES3zz6WYqy8usDiMq3OX2O0bZjSQsQTC1JrEVJSwAs2bNYtasWVaHERF/2fQ2Xxzehak1245vBsCGFSy4Te/1+ZGdR1ociRD2VHT4kNUhRM1pndM4fqDlrTSsHFog0qQNSxBMrQOXFoT9Pb71t7x/6K98UPAiBZWfodxt6ZwRvjtwnn76aU4//XSSkpIYPHgwH330UbPKyUrKYnjH4fx161/DFpsQrUm/sReRlJZudRgxZdOmTQwaNIhBg7x918yePZtBgwbx29/+1uLIWk5qWILgMTUOZ+uqYWnVtMHIrOv485RfhL3ocA9rUO4pp0tal7DHKUSrIQ1uQ2LV0ALRINUGQdCaVtWGJS5E6Asb7mENNJqiiqIwRylE69BaT7z1iqd9bSZJWILg0SaGJCwxREXkLvRIDGtwRc8r2HViFwUlra+XYSHCQY68wq9FCcvcuXNRSnH77bcHpmmtueeee+jUqRPJycmMHTuWL774otFyFi5ciFKqzl9ZmT1ah3tMjVMSFtt69fOPmLroF3zvlTuY8srtaFURke1EYliDoTlDSXIkcc/ae+Lr16QQwYin70Tr6e4rYpqdsGzcuJFnn32WAQMG1Jj+xz/+kUceeYQnn3ySjRs3kpOTw4QJEzh58mSj5WVkZJCfn1/jLykpqbnhhZXWVR2QCft5Lu8Vdpd+yHentrO/dAdJOpfRXQdHbHvhHNagY1pH7hp2F/858B/+9fW/whGeEK2LHHuFT7Ma3RYXF3Pttdfyl7/8hT/84Q+B6Vpr5s+fz1133cUVV1wBwAsvvEB2djYvv/wy//u//9tgmUopcnJymhNOxGlAKljsy9QeUunOhp+8GdHtRGpYg/Fdx3P3f+5mxbcruKzHZdKrpxA+hsNBaVEhf5p2Wb3znS4X197/CO1yW0MfUlLF0pRmJSw333wzl156KRdddFGNhGXPnj0UFBTUuMbvcrm44IILWLt2baMJS3FxMd26dcPj8XDOOefw+9//PnBbltW0jUf6FWBioqLQHKv6sAbf//73A9NXrlzJ1KnN76k2PTGdUZ1HsWrfKt7b+x4Tuk0IQ7RCxL7+4yaQnJ6B1rraJVPvY1lxMR+9vJCTRw63koRFNCXkhGXRokV88sknbNy4sc48/y/P+q7xf/vttw2W2adPHxYuXMjZZ59NUVERjz32GCNHjuTTTz+lZ8+e9a5TXl5OeXl54HVRUeTutNDUvQwg7MPUnqgkLBC5YQ0eG/cY5710HrtO7JKERQif5PQM+o+r//tQcuI4H728EI+nlfQQK6eYJoWUsOzbt4/bbruNFStWNNq+JNRr/MOGDWPYsGGB1yNHjuTcc8/liSee4PHHH693nblz53LvvfeGEn6LKPk02ZbWJoZyRGVbkRrWYG/RXkxtsv/k/jBFKkTrZji9py/T47Y4kvCQM0zTQvpZunnzZg4dOsTgwYNxOp04nU5Wr17N448/jtPpDNSstPQav2EYnHfeeezc2fAItnPmzKGwsDDwt2/fvlB2RbQi0bok5Ddr1iy++eYbysvL2bx5M2PGjGlxmYu3LwZgWu9pLS5LiHjgcHh/pJitpYZFNCmko/z48ePZunUreXl5gb8hQ4Zw7bXXkpeXR48ePcjJyWHlypWBdSoqKli9ejUjRowIejtaa/Ly8ujYsWODy7hcLjIyMmr8RYq30a3kv3blrcGL7S6Fumd2B+Bo2VFrAxEiRihfwqJbS8Ji81OMtkF8IV0SSk9Pp3///jWmpaamctpppwWm33777TzwwAP07NmTnj178sADD5CSksIPf/jDwDozZsygc+fOzJ07F4B7772XYcOG0bNnT4qKinj88cfJy8vjqaeeaun+iThg4sEZ46NMXNHzCh7e+DAbCzYyNnes1eEIYXuG4U1YWk0bFpvQWgfuVjK1Rpsm7koP2ga3MIX9KP+rX/2K0tJSZs2axfHjxxk6dCgrVqwgPb1qAKu9e/diGFW/iE+cOMGNN95IQUEBmZmZDBo0iDVr1nD++eeHO7zm0Vq6ArAxrU2UEds1LMnOZLpndie/JN/qUISICYbDwaCs8ZS+uZ8v3nsLlEKharaXrH6OrX2+bWyeb5qqPtu3jGp0XX9rx6rH6s/XJu5in3EYU9dNsjQm5Hbm97+bW6tM7a3d0IDS9cRaLZWovlytAHWtdeqqNq2e811Rm0OcLCkE2tSzbnS0OGFZtWpVjddKKe655x7uueeeoNd59NFHefTRR1saSsR4Pw6SsdiVxsRoBaNMnJZ8Go4oNR4WItYppeiZOZhSRwnlRqnv1mcTbWq82Ua1Y7by/6mq19Vm1ZkeeKw5XSnlTYz8ZdV47l/Hd74IPFaVefh4MZkJaWS2SaxWqPfBXeHB40klOb19zdBVVQFK1ZxWPTnzPq+5TNVy1dev/lh9frVpCl/y542vrLyUgv3/xJWJpWK7Hl0IwNQmqjWc6LXcjSZEKJTDoNNlA0kb3snqUILyzu8+p1e33kya/j2rQwnJ4cOHWfm3f1o+pl7s/yyNAl0rWRf20lpqWDTN7+JfiLikFJjWt60IlkbXaA4hQiPvXJDkNGJfGhMjxu8SAn9NkXzShAiWMmJrfEQT3SqOVVaRdy4IdmgdLRrmTVhi/5KQRsslISFCoVTMZCxaa6lhaSF554KhpWt+O2stNSxaS8IiRKul/TUs8h1vLml0K2JeheNbTnhaxwCVkhgLERyzzI0uj50+WDb982PcyhPoP0aELvZ/lkaB9+Y0OZHY0alK7wCYRWbsD81gapNlu5fx+3W/tzoUIWyvbPsxAJxZyRZHEpz/fLoBgNyeMrJ0c0nCEgTvaM1WRyHqM/vdJwA4N+0aiyNpuWv7Xku/0/rxzp53rA5FCNvT5d5a1aRebawNJEgKGJR9Ft3P6Wl1KDFLEpYgSQ2LPZV5ytGmg79M/bXVobTYxd0vZlL3SfJZEyIIp7YeBvB1FCfigSQsQfA2hhR25DScKJ1EorN1XBfW1fsDF0I0yNXd2+2qcshpLF7Iv3SQpDGkPSUYDjSx0/CuKXKnkBDBcWQmep9Y3PuqiB5JWIIiVY525TScoFrHHUIgvd0KETT/YTmWvi5yKmkRSViCECP9EsWlBCMBVOupYQFpLyVEUPyjJ0uCHzckYQmKZCx25XIkopSHSk/rSFrkkpAQwdFa2nvFG0lYgiRJvD0lOhOAqv5YYp1cEhIiSB4dY+1XYilWe5KEJQjScZx9uRzehnel4UhYtEZ7PHjcFbgrS6msKKGi/CTlZScoO3UM01PZ8m00GYLU5gkRDG3qGLxDKDa/30ePHgUgPz/f0jika/4gTKh4n//55Gl2f+r/clQlL03d8KxVVapTe9nqrxX1fJRV/dtRTZTlf9678ksMTL51dueUkVaz6Hq/OBql/c/qW6bqtdK6Wpu3mst5X2vvGEy+ef5ppmmC7zZxXW268m1bKY3h23WtHLhVIh4jAY+RiMdIRBve126VgEc5ydV74DS4/PXRpHk3iQmYCl/JGtO3BdM3jzrLeF/rJmo2ztWJvHDd5kaXaSkto7kKIWwmMdH7wzA1NdXSOCRhCcLQxD20SVJ8mzao1qlZ13iqao/rXO2F/8Rd4yTfwMKaxhOCwLK6+mt/YoAvIdAcVCV0rPiGoqTOlBkpDSQ5mjpVlTVO3CrwoKpF4k+aqhZV1R6Ut2ylapatDJRSuJwO7zylvDVXqmpZE4Xb1HhMjfa4wVOOclegzAoMTwXKU4Gz8iQpVOLQbnobiUwvqiCpU08chhNDKZQyvI94t2dgYPi27Z1noPAt45+GUbWeMlAo3zoGoPjznqXsUZG/7CQjNgvResVm/QqkpKQA0KZNG0vjkIQlCGkuJ9ndR5Mz5VGrQ2mWs60OIMLOj8I2vj2xi7eOfx75DWm5/ChE8GI1BYhNVrevk7pnIYIQrSSi1FOKR7eOO56EECKcJGERIkjR+C23et9qSt2lUdiSEELEFrkkJEQQolUV2sbVhvYp7aOyLSFiXgxdEZILvS0nNSxC2IhSivbJkrAIIURtkrAIEQSrG5sJIUS8k4RFiKDU33ONEMIi8hsi7kjCIoQQQgjbk4RFiKBJHYsQwl7WrFnDlClT6NSpE0op3nrrLatDihi5S0i0bvs3w4rfglkJ2j9kQAOPUG0atZY5jk6Wr4sQwl5KSkoYOHAg119/PVdeeaXV4USUHIHj1NNPP81DDz1Efn4+/fr1Y/78+YwePdrqsMJv73rYuw4G/sA3QQWGDwgMHdDUI6BO7YLyAxbsgBCiPgrf74lmWrNmDQ899BCbN28mPz+fJUuWcPnll4crvKiZPHkykydPtjqMqJCEJQ4tXryY22+/naeffpqRI0fyzDPPMHnyZLZt20bXrl2tDi/8EpLh8qdbVsanf0Z/tSg88QghLGdJzUSMj8Zu9WjykrDEoUceeYSf/OQn3HDDDQDMnz+ff//73yxYsIC5c+daHJ09yfg+QrQu8VQz0Vq0qNHt3LlzUUpx++23B6Zprbnnnnvo1KkTycnJjB07li+++KLJst544w369u2Ly+Wib9++LFmypCWhhV8r6YejoqKCzZs3M3HixBrTJ06cyNq1ay2KKjZoaXQrhM3IdzKeNDth2bhxI88++ywDBgyoMf2Pf/wjjzzyCE8++SQbN24kJyeHCRMmcPLkyQbLWrduHdOmTWP69Ol8+umnTJ8+nauvvpoNGzY0NzzRgCNHjuDxeMjOzq4xPTs7m4KCAouiirSWJ5vScZwQNiPfybjTrISluLiYa6+9lr/85S+0bds2MF1rzfz587nrrru44oor6N+/Py+88AKnTp3i5ZdfbrC8+fPnM2HCBObMmUOfPn2YM2cO48ePZ/78+c0JTwSh9glYay0nZSGEELbVrITl5ptv5tJLL+Wiiy6qMX3Pnj0UFBTUuNzgcrm44IILGr3csG7dujqXKCZNmiSXKCKgXbt2OByOOrUphw4dqlPr0iqc2AvushYXo1AcKztGpacyDEE1TGvNfwv+S6UZ2e0IYQe60qRs13HKdjTvD3dsXBI6eaSQY2bDVxlaori4mLy8PPLy8gDveTgvL4+9e/dGZHtWCrnR7aJFi/jkk0/YuHFjnXn+k2B9lxu+/fbbBsssKCgI+RJFeXk55eXlgddFRUVBxR/vEhMTGTx4MCtXruT73/9+YPrKlSuZOnWqhZFFiLvM2wdLC6UlpgHw2ZHPGJw9uMXlNSTTlcknhz5h3YF1jOkyJmLbEcIOSj45yIklu5q9viMjMYzRRM6Gdz4CIDOzTdjL3rRpE+PGjQu8nj17NgAzZ85k4cKFYd+elUJKWPbt28dtt93GihUrSEpKanC55lxuCHWduXPncu+99wYRtaht9uzZTJ8+nSFDhjB8+HCeffZZ9u7dy0033WR1aOFnJED22S0uZmSnkQCY2mxxWY35/cjfM2rRKE65T0V0O0LYga40UQkG2b8Y0qz1jRZ05lhcXMyuXVXJkr9mIisrK/zdO5iaRJyM+1H470oaO3as5bcbR0tI/9qbN2/m0KFDDB5c9QvT4/GwZs0annzySbZv3w54a0w6duwYWKapyw05OTkhX6KYM2dOIJMEbw1Lbm5uKLsTEk3rGWtr2rRpHD16lPvuu4/8/Hz69+/PO++8Q7du3awOLfyUIhx3EkT7DiFDRs0Q8UADSuFs44r6pqNZM6GUfJ/DIaSEZfz48WzdurXGtOuvv54+ffrw61//mh49epCTk8PKlSsZNGgQ4L2NdvXq1cybN6/BcocPH87KlSu54447AtNWrFjBiBEjGlzH5XLhckXvQ95akhW/WbNmMWvWLKvDiAIVls6a/DUrRpQOPNIAWsQFrS07uEazZsJQSrpFCIOQEpb09HT69+9fY1pqaiqnnXZaYPrtt9/OAw88QM+ePenZsycPPPAAKSkp/PCHPwysM2PGDDp37hzopOy2225jzJgxzJs3j6lTp7J06VLee+89Pv7445bun4h3YaphiVbC4j+ASkd1QrQeSilMSVhaLOw93f7qV7+itLSUWbNmcfz4cYYOHcqKFStIT08PLLN3714Mo+rAP2LECBYtWsRvfvMb7r77bs444wwWL17M0KFDwx2eiDvhqWEp93gbeCc6ItvIz/8rTBIWERda07X2RhjKkBqWMGhxwrJq1aoar5VS3HPPPdxzzz1BrwNw1VVXcdVVV7U0HBGPCvfDsa/BmQROl3fsIKfL+7riJJjuFm/Cn7CsO7COr098XWOeqc1ADYypTUxMtNaB6Zpqz7UOzPdP11qT6EjE5XDh0R5voXFwEBciXjIWwzBiuobFLpeoZSyhoMTuBy0uvP5j2Le+4fkd+rZ4E5muTBKNRB775LEml1UoDGWglMLAqHquDG9jWkXguf9AUOmppNxTToVZgUM5aJ/cvsUxC2F3Oj7ylcD33DTNGlcXRGgkYQmGhrj4VsWqylPQ/yoY/Qtvvyvu8pqPp53Z4k30yOzBhms3BGpG/DTam5D4kxRUi36NmNrEY3pIcCS0OGYhYoFNfrxHlMPX9i1ebj+OFElYghUP36pYltwGsltek9IYpxH5r4uhDAyH/AITojWpXsPicDgsjiZ2yZExKHFSbxmz5FeLEDEpXr66cvoIC0lYgiU1LEIIEX5yaBVBkoQlKPHyMyCWyVFPiNgjx1YRPElYghEvTdmFECLqWv+x1Z+W2eX24FgljW6DJR+0+p06BpueA09jfZ1o7906ZYVQVuR9LC+qeu2pAMNZ7c/h+3OCMgDle/+V79hW/bWCI7sgd1g09lYIEU5SwSJCIAlLMKSGpWE7V8IHf4D0jjT6HjldkJTp+8uAjI7g8r12JID2gOnxdvIW+DO907UGtPdRm1XP/Y85A2DgD6Kzv0KI8IqjQ2us17BYfVu2JCxB8HbDEtsftIjx98x6+1Zv4iGEEMGKkxoWLaePsJA2LEGK9cw4YgIZt7w/QghRL+kwLiwkYQmKfNga5ntvJKETQoj6+Q6P8sO3ZSRhES0jNSxCiJaQQ4cIkiQswZAKlkZIDYsQopni7FKJ1LC0jCQsomXi7IAjhAi31n8Sl35YwkMSlmDJB60BUsMihBAi8iRhCYrUIjRIaliEEC0RB791tJxDwkISFtFC0qmeEKJ54ur3Tjzta4RIx3GxYOvrcPgrb++vtb/hdS7FqODmm5XebvW1WbObe5S3O/xgpqHh4OdyOUgI0WxxcfRQcbKfESYJS1AsrkX4523esXWS2/rG1vGp8/Ok1uum5hsJkHKad7o2a3Z3X/uxvmn+xKXPpS3eRSGEaLW83aWjtY7Jhrd2iVkSlligNVzw/2D4LKsjEUKI8LLHuTCiAl3zyxX0FpGEJVjb3oKDXzSxkIZhN8MZF4IhzYOEEKJR8dKIJV72M8IkYQlG78lw5Luml/tyGez+wPvccILD5R2l2OkCR2LjgwM29oGuLAktXiGEiBnxUeWgAv8RzSUJSzD6XAadRza9XMHn3loYTzm4y8FTUfPRrKTRT2xD1wmVA86a0qzQhRBCWEv7fpDapS1IrJKEJZxy+nv/hBBCBCcOzuFyQSg8pKGFEEIIa8TLmVyDiofMLMIkYRFCCCEiSRrdhoUkLEIIIUQkSb4SFtKGRQghhHXi4EqJRje4m1prTNNEaw+m6cY0PWjtffS+duPxuGtO0x60b573uXe61h5MXbWeNj1V87X3dWA72vvcPw9t1pimddVfeXkZ7U7bi8dTHNX3rTZJWIQQQljGU1hBwaObgeo3SqoaD9SaXO8dlaavGkPrQIfc3l65fc/902stG+jAG83+M5+kPGU/Gg8YHrTy/eEBZaKV/9Gk0WoTVXOe2V4ztL3Je+//vdpUbctRTUzT24O51gZa+4dhUaRnu9F8AZxlWWySsAghhLBEyqAO6ApPPaOK1J5QY2bdeQpvEqOq3TpcbZr/ubcvlJrT/JNQiiK1nnTOIYUzUMqJwuH9U85qrw2UcjQ+jpv2v/bGWul2c6j8OI70RF8chi9Ww9sYVynfc4f3UTnAtx3D4fQ+KgdKOVCGw/faiTK80w3Du4zyPTeMqmmGw4nD8Mbv8JXlcCQElqt67p9fN4tyu0vY+e9zSE52NfhvGQ0hJSwLFixgwYIFfPPNNwD069eP3/72t0yePBmAgwcP8utf/5oVK1Zw4sQJxowZwxNPPEHPnj0bLHPhwoVcf/31daaXlpaSlJQUSnhCCCFiSEKHFNpMOcPqMKp8oOnc+yo6d/5B2Iu2rl6i5QJJjMWNh0NqdNulSxcefPBBNm3axKZNm7jwwguZOnUqX3zxBVprLr/8cr7++muWLl3Kli1b6NatGxdddBElJY331JqRkUF+fn6NP0lWhBBCCDuoPhiSdUKqYZkypWZvq/fffz8LFixg/fr1JCQksH79ej7//HP69esHwNNPP02HDh145ZVXuOGGGxosVylFTk5OM8IXQgghwsiODUss531PtMUJS7Nva/Z4PCxatIiSkhKGDx9OeXk5QI2aEYfDQWJiIh9//HGjZRUXF9OtWze6dOnCZZddxpYtW5rcfnl5OUVFRTX+hBBCCBFeMXlJCGDr1q2kpaXhcrm46aabWLJkCX379qVPnz5069aNOXPmcPz4cSoqKnjwwQcpKCggPz+/wfL69OnDwoULWbZsGa+88gpJSUmMHDmSnTt3NhrH3LlzyczMDPzl5uaGuitCCCEEUG28n3i4zzpk9rgkFHLC0rt3b/Ly8li/fj0/+9nPmDlzJtu2bSMhIYE33niDHTt2kJWVRUpKCqtWrWLy5Mk4HI4Gyxs2bBg/+tGPGDhwIKNHj+bVV1+lV69ePPHEE43GMWfOHAoLCwN/+/btC3VXhBBCCNEk/yUh09IoQr6tOTExkTPPPBOAIUOGsHHjRh577DGeeeYZBg8eTF5eHoWFhVRUVNC+fXuGDh3KkCFDgi7fMAzOO++8JmtYXC4XLpe1t1gJIYRoLfy1B1LDUpf/kpC1UbS4a36tdaD9il9mZibt27dn586dbNq0ialTp4ZUXl5eHh07dmxpaEIIIUSQpP/8hijlTxVi6C6hO++8k8mTJ5Obm8vJkydZtGgRq1atYvny5QC89tprtG/fnq5du7J161Zuu+02Lr/8ciZOnBgoY8aMGXTu3Jm5c+cCcO+99zJs2DB69uxJUVERjz/+OHl5eTz11FNh3E0hhBAiGFLDUpc92rCElLAcPHiQ6dOnk5+fT2ZmJgMGDGD58uVMmDABgPz8fGbPns3Bgwfp2LEjM2bM4O67765Rxt69ezGMqoqdEydOcOONN1JQUEBmZiaDBg1izZo1nH/++WHYPSGEEKJpgd51JV+pw3+XkNW3NStdpw/k2FRUVERmZiaFhYVkZGSEtez/7P8PIzuPDGuZQggh7MM03Xy4qjdnnTWPTh2vsjoc23ny7Z58/5z76Nz5mrCXHez5u8VtWIQQQojYZ4/bmtesWcOUKVPo1KkTSineeustS+OpoiyvYZGERQghhLCJkpISBg4cyJNPPml1KDXUNyhitMlozUIIIYRNbmuePHlyYEBhe1Gx19OtEEIIIeKNwuq7hCRhEUIIIWxSw2JfyvKebiVhEUIIEfdax/2yEaSw/E2ShEUIIYTws0HjUnuSS0JCCCGEDUgVS+Osv61Z7hISQgghfKzuh6W4uJhdu3YFXu/Zs4e8vDyysrLo2rWrZXFZ/b6AJCxCCCEEdqlh2bRpE+PGjQu8nj17NgAzZ85k4cKFFkXlu1KmrW10KwmLEEIIEWBtTcLYsWOx44g5Wlt/SUjasAghhBA2qWGxK29Pt5KwCCGEEMLu5LZmIYQQwlqByzByW3MDpIZFCCGEsAG5JNQ4ZXnbGklYhBBCCB873L5rS9KGRQghhLADqWFpmiQsQgghhE1IDUv95LZmIYQQQticUkruEhJCCCFsQ+4SaoDUsAghhBCWs/oOGLtTcluzEEIIYSdSw1I/uSQkhBBC2ID3ZCy3NTdGEhYhhBDCUm53odUh2J60YRFCCCEstnbdOAAMR5LFkdiTUgZo09IYJGERQggR97LajvQ9jrI4EjuztobFaenWhRBCCBtIST2DisqjGIacFuunLO8LWGpYhBBCCNEEua1ZCCGEEHankNuahRBCCGF3Co21jW7lYp0QQggRo7TWuD3lnPKUU1xZRpm7jEqznHJ3GZWmh0pt4jY1lRoqtWZHKRx3w8AUDxrQ2kQDJiZoAs+19pZtotFas83dhXM91qYMIW19wYIFLFiwgG+++QaAfv368dvf/pbJkycDcPDgQX7961+zYsUKTpw4wZgxY3jiiSfo2bNno+W+8cYb3H333ezevZszzjiD+++/n+9///vN2yMhhBAiRN9UprO4+Hxe+O/ruE2o1Ao34NaKSq3woDA1eHsj8TdA1aD9Y+xUNUrVUPN5tSsp2tcWxESRgIcMdQo3Bm4ceLThfa4duDHw+Ka7tQMPqtY8R9U8ldDAXinA0cC8htZpYGnzEpJOtWdISGuFV0gJS5cuXXjwwQc588wzAXjhhReYOnUqW7ZsoW/fvlx++eUkJCSwdOlSMjIyeOSRR7jooovYtm0bqamp9Za5bt06pk2bxu9//3u+//3vs2TJEq6++mo+/vhjhg4d2vI9FEIIIZrwgWcIK1QKnU8dwalM7x+aBLzPHcqbpvj7wVVo7ziJyt+Zv67RR65S/hTG23dunfXQlGsnJ8z2vu1pkjBx+LerPDhx41QapzJJUAqnUiQYDhINRYJy4DQMXIaDRIeDFIeDZIeDJCORREcCiY5EEgwHCUqRYBi+dQ1KPODRig6JBgoDQxkYClAGBgqFgTKU77lCKQOlFJes/QJX+oDo/GM0QOkWjviUlZXFQw89xOjRo+nduzeff/45/fr1A8Dj8dChQwfmzZvHDTfcUO/606ZNo6ioiHfffTcw7eKLL6Zt27a88sorQcdRVFREZmYmhYWFZGRktGSX6vjP/v8wsvPIsJYphBDCPu7ZtZ/3jhbx8dCzrA7Floa9/wqTuo3h3jM7h73sYM/fzW506/F4WLRoESUlJQwfPpzy8nIAkpKqegl0OBwkJiby8ccfN1jOunXrmDhxYo1pkyZNYu3atY1uv7y8nKKiohp/QgghRHN460JEoyzuiCXkhGXr1q2kpaXhcrm46aabWLJkCX379qVPnz5069aNOXPmcPz4cSoqKnjwwQcpKCggPz+/wfIKCgrIzs6uMS07O5uCgoJG45g7dy6ZmZmBv9zc3FB3RQghhPCyule0GGD1WxRywtK7d2/y8vJYv349P/vZz5g5cybbtm0jISGBN954gx07dpCVlUVKSgqrVq1i8uTJOBwNNfrxUqpmXqu1rjOttjlz5lBYWBj427dvX6i7IoQQQgDWn4ztzg61TyHfo5SYmBhodDtkyBA2btzIY489xjPPPMPgwYPJy8ujsLCQiooK2rdvz9ChQxkypOF2xTk5OXVqUw4dOlSn1qU2l8uFy+UKNXwhhBCiDu+9P3Y4LduUagWjNWutA+1X/DIzM2nfvj07d+5k06ZNTJ06tcH1hw8fzsqVK2tMW7FiBSNGjGhpaEIIIURQNNBExX7cs7oWKqQaljvvvJPJkyeTm5vLyZMnWbRoEatWrWL58uUAvPbaa7Rv356uXbuydetWbrvtNi6//PIajWpnzJhB586dmTt3LgC33XYbY8aMYd68eUydOpWlS5fy3nvvNdpQVwghhAgnre1x2cOu7PDehFTDcvDgQaZPn07v3r0ZP348GzZsYPny5UyYMAGA/Px8pk+fTp8+ffj5z3/O9OnT69yavHfv3hqNcEeMGMGiRYt4/vnnGTBgAAsXLmTx4sXSB4sQQoiossNJec2aNUyZMoVOnTqhlOKtt96yOiTAFkMJhVbD8txzzzU6/+c//zk///nPG11m1apVdaZdddVVXHXVVaGEElVWX7cTQggRWXa5rbmkpISBAwdy/fXXc+WVV1odTg1WnwllLKEgSEMsIYRo3ezShmXy5MmB4W7sxAZvjYzWLIQQQlhde2B7yvr3SBIWIYQQcU9rua25KZKwCCGEEBazSxsWu1I2SBesj0AIIYSwAUlYGqYA0zQtjUESFiGEEHFPg2QsTbD6jlm5S0gIIUTcs0vHccXFxezatSvwes+ePeTl5ZGVlUXXrl0ti8sO740kLEIIIQT26MJi06ZNjBs3LvB69uzZAMycOZOFCxdaFBW+e76lhsX2rK4GE0IIEVnewQ+tN3bsWLTVXcrWS2FtCxZpwxIUO2TdQgghIseOKYKd2OEsKAmLEEKIuGeXnm7tS6FNa9M6SViEEELEPbs0urUrhUJbfFFIEhYhhBBxTzqOsz9JWIQQQsQ9b6NbSVkaomQsISGEEMJ60oalKQrT4pRFEhYhhBBxT9qwNE7ZoB8WSViEEEIIJGFpjMKb1FlJEhYhhBBCNM3ijEUSFiGEEHFv3Yliq0OwNYUhjW6FEEIIK53ymOwvr7S863k7U0phSj8sQgghhHXKTe+J+MYu7S2ORDRGEhYhhBBxrcLX5XyiIc1uG+K9R0jasAghhBCWqfA1JnUZckpsiEJZ3eZWEhYhhBDxrcJ3SUhqWBpj/XvjtDoAIYQQwkqBS0JKobWm0tSUuj2crDQpqXRT6jGpcJt4TM3J0koqPSbt0lwAKB34Dw6lMBQ4DIWBwlAKh4H3UYFhGBjge+5f3ruOUiowPIBSgFKBnndNrXGbGo8Jbq3xmCamBo+p8Zgat9beZTwaj/ZO8z+a2nshx9S1L+lUDUSg8Mbge0GgizjtfdRoiosrMNM9kfxnaJIkLEIIIeLaoaIyXKsLuOK9A96+Rkw71CfYi5F0kITubeAc62KQhEUIIURcy3CDKvMw7JwcTst04XI6cDkMkpwGyU4Dl9PAaRg4HIr8Y6WcLK3kzM4ZVQX4BgY0zaraDO9zjUdXn+6r8dC+ZbQOzAN81Rne+do3frQ2dY2aGsNQ3hocXw2MwzfNaXhrSfw1N4HaG996vjADj5qqjvZNX3WK/7XWVeMq+dd8aNl+eiYmhP/ND4EkLEIIIeKaw3c95LdjetK3U0YTS8enJetSSbB4dEhpdCuEEEKIRilk8EMhhBBC2J4kLEIIIYQQTQopYVmwYAEDBgwgIyODjIwMhg8fzrvvvhuYX1xczC233EKXLl1ITk7mrLPOYsGCBY2WuXDhQpRSdf7Kysqat0dCCCGEDa1Zs4YpU6bQqVMnlFK89dZbVocUEqsHPwyp0W2XLl148MEHOfPMMwF44YUXmDp1Klu2bKFfv37ccccdfPjhh7z44ot0796dFStWMGvWLDp16sTUqVMbLDcjI4Pt27fXmJaUlNSM3RFCCNGa7Tt2ire27Mfju5umuqo7W6oah3qX8/dJQo3nptaUVnj47sQpIPJdz5eUlDBw4ECuv/56rrzyyohuK/yU5V3zh5SwTJkypcbr+++/nwULFrB+/Xr69evHunXrmDlzJmPHjgXgxhtv5JlnnmHTpk2NJixKKXJyckKPXgghRFx5ddM+nvpwF+3TfR23+ZIT/8m0ehKj8d726zC8twAb1Z77b/tNSnSQkeTkqsFd6NEuLaKxT548mcmTJ0d0G5Fi8Q1CQAtua/Z4PLz22muUlJQwfPhwAEaNGsWyZcv48Y9/TKdOnVi1ahU7duzgsccea7Ss4uJiunXrhsfj4ZxzzuH3v/89gwYNanSd8vJyysvLA6+LioqauytCCCFiRKVHk5uVwupfjrM6lDhjfcYScqPbrVu3kpaWhsvl4qabbmLJkiX07dsXgMcff5y+ffvSpUsXEhMTufjii3n66acZNWpUg+X16dOHhQsXsmzZMl555RWSkpIYOXIkO3fubDSOuXPnkpmZGfjLzc0NdVeEEELEGK11oCM0EW0xdEkIoHfv3uTl5XHixAneeOMNZs6cyerVq+nbty+PP/4469evZ9myZXTr1o01a9Ywa9YsOnbsyEUXXVRvecOGDWPYsGGB1yNHjuTcc8/liSee4PHHH28wjjlz5jB79uzA66KiIklahBCilfOYGhmj0Aox1oYFIDExMdDodsiQIWzcuJHHHnuM+fPnc+edd7JkyRIuvfRSAAYMGEBeXh4PP/xwgwlLbYZhcN555zVZw+JyuXC5XKGGL4QQIoaZGqlhsYAd3vEW98Oitaa8vJzKykoqKysxjJpFOhwOTN/Q3cGWl5eXR8eOHVsamhBCiFbG1DrQlb6IJu9I1lYKqYblzjvvZPLkyeTm5nLy5EkWLVrEqlWrWL58ORkZGVxwwQX88pe/JDk5mW7durF69Wr+/ve/88gjjwTKmDFjBp07d2bu3LkA3HvvvQwbNoyePXtSVFTE448/Tl5eHk899VR491QIIUTMM2O4DUtxcTG7du0KvN6zZw95eXlkZWXRtWtXCyNrmrJBHUtICcvBgweZPn06+fn5ZGZmMmDAAJYvX86ECRMAWLRoEXPmzOHaa6/l2LFjdOvWjfvvv5+bbropUMbevXtr1MKcOHGCG2+8kYKCAjIzMxk0aBBr1qzh/PPPD9MuCiGEaC08psaI0T7aN23axLhxVXc3+dthzpw5k4ULF1oUVShiqIblueeea3R+Tk4Ozz//fKPLrFq1qsbrRx99lEcffTSUMIQQQsQpU3v7UIlFY8eOtfyySvMpy3u6jdE8VQghRDwyTY2K0YQl9sngh0IIIURQPNLo1iIyWrMQQggRNG+jW6ujiEdySUgIIYQImmnG7l1CscwO77gkLEIIIWKGdBxnHa2D71MtEiRhEUIIETM8WvPN0RKrw4g7SimsTVckYRFCCBFDikoryS8s41SF2+pQ4oohjW6FEEKI4F09xDvIrdu0uglofFFKWZ2vSMIihBAidsgtzdaxerRmSViEEEII0SSre+mVhEUIIYQQjVLKwOprQiGNJRSvrK4GE0II0Xpp0/T+ob2P2kRr7XutAQ1aozVoTLTpm6d9tR7lxaAU2pmCVuCvCNF4X2jfbeDe9f0bBdPXjlajvOc5DWb1ZQMLKzyV5WiHK3pvSj0kYRFCCBEzFm/cB8C5962kdncs/2e8zCWOjRjK2y9rVd+s2tvxma6apvzT6nldtUzt1xonHlIpw0RRoZ01OlSrvr2qaXXn+2PzN8dR2KNjtsbMdzpYm3kxcJllMUjCIoQQImbsPlxM+zQXHdJdgbO8Ut6nQw9/QaWRREH2GMA3EUX1zEZhBGocFKCVEShEVV/H/1ypamUoFJDgOUVlQhoeI5Hq6YbyrasCiUjVtr3b8q7fd89C0kr389/+d4MyqpVvoA3fdnzTVaB473zvzTrKe9eOr7yso5vRRiInsgZU7bK/ekRVj9CXLFVLlLx0tfnVNufdknfaV89wTtvyoP+dIkESFiGEEDHDaSguHdyZOZPPqjNvxx+cHE3vxYj/fcKCyELw1xVwoIDzr/pFmAr8cZjKadj+g/+k3OJWr9LoNgjK9pV1QggRH5RSNHSzirZB52atlR3OgpKwBMnq27mEEEJ4r5w0dDz2XsCQY3Uk2CEVlIQlCFlJWRwrO2Z1GEIIEfcMqWGxhNSwxIiOqR3JL8m3OgwhhIh7Cu+IzfXRqKrGpiLstMWjZEuj2yBkujL54ugXVochhBBxQ2uNx9S4TU2lx8Tt0VSaJh5f/yT1i5EaFqVosJrIthp736NDEpYgKIuzSiGEiCfTn9vARzuPNDh/Qt/seqfr6rfzirCyQyooCUsQvtt+nJWvfUHioE4kuBxAreQ40KugrvG6uvoaiSlf5wH+e/+9t9VX3SBf/Z5+pcA0QZsa06zWXWG1LgZqJFa11q/aJoEVak5XgYuUweZnzgQHPc5tj8MhVxaFEOHz9eESLuzTgcn9c3A6FE7DIMH36HAoBndr28CadjitBiP2fgTboTmzJCxB+OazI5QWV/Lff+7xJix1Ot2h3iSgap7/oXo3Pdrf27K362TvRO+jWf111XLKAMNQKMPXaVDt9ar6Y66zPrWW889vqZTXErn2vmEkJslHSYjWqMJtctWf16I1fG9gJ1ZsK2D34RImnJXNz8aeQfd2qRHZbr9OGfzPkNyQ1jExbHBabZ3skGLJWSYIuWdlwWaYOXckaW2tHUshUrRvkIlA4lNP5qVqLb90fh4Hdp6g6EgZ7bqkRStUIUQUFZVV8tl3hQBsP3iSrJREzuqYzuJN+1i8aR+zJ/SiZ4c0frfsCzTwm0vPon2aC6fD4LzubeWSen1i9j2RRrcxQYWrSsKmqi5PQTAfSoVixBVn8vq8Tez94ijH80tAQWobF53ObBPhaIUQ0WL6am6fmzmE8WdVtR155b97eeW/e1mwajellZ7A9NsW5QWe9++cwb3f68fOg8WM7tWetEQnbtPE9A3ad+hkOcmJDhIMg0rT17DWY1LhMZsVq3+wPxF+3ott0ujW/mycDM+dO5c333yTr776iuTkZEaMGMG8efPo3bt3xLednJ6A4VSsW7I7ME0puPHxC3AmOCK+fSFE5PnP/0atWoFrzu/KNed3pbC0kq/yi6jwmLRJTuTQyTKyM5I4fqqC//3HZq5csK5Z2011NeP0pOzQ0iIYNj6pNERbna5IwhLzVq9ezc0338x5552H2+3mrrvuYuLEiWzbto3U1MhcW/bLaJfMjY9egMf3a2jnxoOsemm7DGUgRCsSGEOvga91ZnICQ3ucVn1K4Nn7v7iAb46cIicziS8OFOJQCsNQvkf48KvD9OmYTvfTUnEaCqfD27g2wWHQs0Pol5ljpuM438CCscQO76wkLDFu+fLlNV4///zzdOjQgc2bNzNmzJiIb9+RYOBI8N4ltO9Lb2/AyiEJixCthf+SUO0almB0zEymY2YyAKfX0zj3wj71357cElLDEhl2iFjuRw1BLFwaLSz0No7LysqK+rZT0hMB751MQojWwZ+wxEI70di5SygG3sx6WN3TrSQsQYiVj5bWmtmzZzNq1Cj69+8f9e1ntE/GmSgfKSFak4basNhT+BrdLliwgAEDBpCRkUFGRgbDhw/n3XffDUvZkcj+1qxZw5QpU+jUqRNKKd56662wlm+HS/1ydmlFbrnlFj777DNeeeUVS7aflJqAu8KkosxtyfaFEOEXSzUsKbqEZE9xWMrq0qULDz74IJs2bWLTpk1ceOGFTJ06lS++CMcwLeF/M0tKShg4cCBPPvlk2MsGe9wlFFLC0lTGWVxczC233EKXLl1ITk7mrLPOYsGCBU2W+8Ybb9C3b19cLhd9+/ZlyZIloe9JhGmbf1lvvfVWli1bxocffkiXLl0siaHoaBkAxcfLLdm+ECL8zBiqYeld+SU9T30SlrKmTJnCJZdcQq9evejVqxf3338/aWlprF+/vuWFR2AsocmTJ/OHP/yBK664Iqzl+tmh0W1ICUtTGecdd9zB8uXLefHFF/nyyy+54447uPXWW1m6dGmDZa5bt45p06Yxffp0Pv30U6ZPn87VV1/Nhg0bWrZn4WTj76nWmltuuYU333yTDz74gNNPP92yWPZtOwpA2+wUy2IQQoRXoIbF4jiCUaQyOO7sEPZyPR4PixYtoqSkhOHDh4ehxFh4N+thcUPOkBKWpjLOdevWMXPmTMaOHUv37t258cYbGThwIJs2bWqwzPnz5zNhwgTmzJlDnz59mDNnDuPHj2f+/Pkt2rF4cfPNN/Piiy/y8ssvk56eTkFBAQUFBZSWlkY9ltRMby/AuzYfYveWQxQdjX4MQojwCrRhiYHG9LsTerEvuU/Yytu6dStpaWm4XC5uuukmlixZQt++fVtecAzUVtWhVGxdEqquvoxz1KhRLFu2jP3796O15sMPP2THjh1MmjSpwXLWrVvHxIkTa0ybNGkSa9eubXT75eXlFBUV1fiLtPoGMLTaggULKCwsZOzYsXTs2DHwt3jx4qjHMuaa3qS2cbHiuS9Y/sznvPS79ZSckMtDQsQyHeYalkg2ZlVK+/piCY/evXuTl5fH+vXr+dnPfsbMmTPZtm1bGEqOvYRFKcPyc2DI/bBs3bqV4cOHU1ZWRlpaWo2M8/HHH+enP/0pXbp0wel0YhgGf/3rXxk1alSD5RUUFJCdXfNe/OzsbAoKChqNY+7cudx7772hht8sdmgd3RCrP0DVpWQk8sN7hlJ8rJyN7+xh16ZDvP7HTWR1TCUl08XIK88kKTXB6jCFECEIDAwfpsOgv2nBmWeeCcALL7zA1KlT2bJlC/369WtZ4WHujTUxMTEQ55AhQ9i4cSOPPfYYzzzzTMsKtu8ppUHehMXT9IIRFHLC4s84T5w4wRtvvMHMmTNZvXo1ffv25fHHH2f9+vUsW7aMbt26sWbNGmbNmkXHjh256KKLGiyz9uBYWusmB8yaM2cOs2fPDrwuKioiNze0kT1DoeyTF9haYpKTrE5Ohn//DLK7Z1DwdSGmR/PV2nwMh2LcteGrrhVCRFN4zrJTpkyp8fr+++9nwYIFrF+/vsUJi7dhaOSyAa015eVhqDWOwUtCygbjNIWcsDSUcc6fP58777yTJUuWcOmllwIwYMAA8vLyePjhhxtMWHJycurUphw6dKhOrUttLpcLlyvKIydL0hK0jNOSOeeiroHXH726g88++I7TB7SjW//T6k1ITxWe4IOFz1JZVooy/GMRaXqcex4Dxl8cpciFENVF8hzl8Xh47bXXwtaYVaExw5Sw3HnnnUyePJnc3FxOnjzJokWLWLVqVZ3exZsn/AlLcXExu3btCrzes2cPeXl5ZGVl0bVr10bWDI5SRuwlLLX5M87KykoqKysxjJrNYhwOB6bZ8Mibw4cPZ+XKldxxxx2BaStWrGDEiBEtDU3YyKAJ3fhqXQFvP/UZHc/I5JKfDSApreblofxdO9i+dg1tcjqS1cl7a/bXn2xk96YNlJ86Rb8xF5KS2caC6IWIX/6LLOGsFGisaUFLhLNZ6MGDB5k+fTr5+flkZmYyYMAAli9fzoQJE1peuAr/TcKbNm1i3Lhxgdf+KxAzZ85k4cKFLd+A8qaDVgopYWks48zIyOCCCy7gl7/8JcnJyXTr1o3Vq1fz97//nUceeSRQxowZM+jcuTNz584F4LbbbmPMmDHMmzePqVOnsnTpUt577z0+/vjj8O5pS8Re7Z3tpLV1ccMjo/nmsyMs/8vnbFr+DaOu6lljGX+ty1V3/Z7MDjkAuCsr+eBvC1jz4t/45J2l/PTJv2E4ZCRoIaItnIfBxpoWtIQCtApPf6jPPfdcWMqpX/hPKmPHjo1om0allOVtJkNKWJrKOBctWsScOXO49tprOXbsGN26deP+++/npptuCpSxd+/eGrUwI0aMYNGiRfzmN7/h7rvv5owzzmDx4sUMHTo0TLso7EIpxekD23PO+Fy2rt7P0O/1ICGxKvlwJHhrXNyVlYFpzoQEJv7vz1GGwdb3V6C1CUjCIkS0ROIcFanGrAozom1YwiYG27BAjCUsTWWcOTk5PP/8840us2rVqjrTrrrqKq666qpQQhExLLN9CpVlHk4eLSOrY9UIriePHAag8GABp3Wu2YBaa43WJpVl5TjS5E4jIaKtqRshWiJsjVmDuGHDHmJvVBylHJb3w9LiNixxIRY+/zHk4Ne7qDy1mtKTXTiV0oHPV73Hro3ryN+5nc59+pLbf0Cddc6f+j9sW/0+W5b/k+FXXWNB1ELEp3D/qI5kY1atdUwMIRCLNSxKKdAx1IZFhG7lr15i/xF/jUDdysr6hkJXvmUDr1XVukprUDqwjL+8QNdOqtocpajR5ZMGNw4Gj2xD/+vD0HCsGbZ+uIlP3v4jAIvu3hyYnpCUTJez+nP5r+4mIbHu3V9pWafhcbvZueE/krAIEUWa8HYcF8nGrBrtvZtFhJ8ypIYlFpza8F8A/j3nVRISG/8yVP9Sm6bJAZ2LM6GC09ue8E7UvgOA9rVn9//7a/+DRmvlX7Bqlvb14KiV79GblOiqBaqSH61Rgdbc1Q42Cr6t6MJ/1xyl8/C9tO3T8lvdQlFRVs6qv/8VgB/NfYodG1aRv+Mreg0fzTkTL2l03d2bvGNLDZkSmYG9hBCNC1elQEQbs2qNioEhBGKx2j4m+2GJR2llB8ko2oOn/CxMlVRjnq7zpNoH0UigvXGIC34yiOzzekch0qYd/O9XLH2mmKUPb2Tms7lR+3Ifzz/CK7/7PRWnvqP/uOlk9+jG3xYf4M1/vcdXDz9JcnIyI0aMYN68efTuXfe9Op6/H4CMduEf2EwI0TAbdabdNK0xYqGGJSYvCcVg1/zxqM3A3pz+1jyuePY2EiPYm25D5s6dy5tvvslXX33V5Im9Kdnn92HMzv28/5Fi70fb6HZBzZ4lTY+H7W9uwHOqlL4/GktlcRnaY3Jixz52v/c5hUfKweEgt397zg7hstLOTdsoLdzN6edeyqSbpgGwevVqbr75Zs477zzcbjd33XUXEydOZNu2baSmptZY/5yJl7J703re/9sCZjz0ZIw0rBOi9bDzECV+MdOGJQbey9qUDQY/lIQlBoRyYg9GjynDeP+jDRxYv6NGwlJ5qoxPnn6XTbsyAcXHH6/AqSsod6YDYJiZJHlOciohi71ryzn94hOkdWwT1DZPFBwEoPeIYYFptRvZPf/883To0IHNmzczZsyYGvOS0tLofs5g1r+xCK1NlJJbm4WIppjIA4iRS0Kx8WbW1Bp6uhWRF8qJPRiJGamknzrAJ3s6cfp/v6J4/zE+W76TfJULZJJt7ierfQJfHu2A4XYDkJ1whO/94RISM9M49tkuXn/8S169630SnCbjZ5xFp1H9G93mVx97R2PtPfzsBpcpLCwEICsrq975p06cAKCitJSk1LQQ91oI0RyxdElIaxMjFn7MeCqbXsZ2pIZFNENTJ/ZgXHzbebz+zDe88bcDACR4TiNJFWPoSr73yBU4UpMZtP84bXKzcJdWkJBSdedO1oAzGT56L3kfnaLIaM9bfz9Amxe3cdmdY8noWrONyddbvmLpw/dhuos499Kf4HTW/5HTWjN79mxGjRpF//71Jz/9xl7EZ+8v55mbZtKp91lMvnk2aW2b/x4I0Zp9V1aBBnKTEltUzuHisvAEFGHaNBnITrYbLRzxORp2rbQ6gpAp5fB13GkdSVhiTDAn9mB0GNybs3M/o/BQKV3Pbk+/6ybhSKzZIVvbrqcB1EhW/M6eeSFnz4QjW7aT94+17C7qwNJ7P2DK/xtFm57ecYC+2bqDJQ/+GsOZTpd+Exh9zWUNxnPLLbfw2WefNTokQ8czezHljv9H/q4dfPnxKl74v5u54YnncKWkNOctEKLVWnGkkJ9+8Q3lpmZkmzSmdczi0vaZpDZjWIsKt/ck1T49yoPNhqi8vJQk4JSzjdWhNE2bkBBbxy2lkBoWEZpgTuzBGn33/7S4jHaDenPRoN50/+cGVvwrkVfnbeG6hzNJbJNO/s69gIc+Iy9l8qyG+0659dZbWbZsGWvWrKFLly4NLqcMg17DRtFr2CgGjJ/E327/Xz55Z6n0yyJENQv3H+Gund8x6bRMJrXL5NWCY/z8y73M2WEwpX0bpnXMYlhmatAN1/2XhJKcNr/U4gvU0+4siwMJUqdBVkcQEjuM1hwD938JP/+J/cMPP2z0xG6FM6cMZdQoF5XOVN74v6Uc3fYtlWXe67RJDTQM1lpzyy238Oabb/LBBx9w+umnB729th0706H7GXy9ZWNY4hci1rlNzV07vuP/7fiO6zu349l+3ZnWMYs3Bp3Jf4edxazcDqw9Ucz3t+xi2Pov+dOeAvaVVVgddtgEbrmNxQatMUD6YRFB0Vpz6623smTJElatWhXSiT2a+nz/PA5ufoWvTjp44Q/3oj2HSG3bk9HXXFzv8jfffDMvv/wyS5cuJT09nYKCAgAyMzNJTk5udFtHv9vLsf376HD6GWHfDyFiTWGlm5u2fcua4yeZ16sLMzu3qzG/a7KLX5yewx3ds9lQWMLi/GM8te8QD31TwCjfJaNLGrhkZPjuuvHYvPVtoH1FTCQssRBjLcpAI21YRBNacmKPpsS0ZCbM/zG7r7yMCidk5Z7P1DtuxJlYf6O/BQsWAN5h0at7/vnnue666xrcjruigoW/mAVA3zEXhiV2IWLVzpIyZm7dw9FKN68MOIMxWekNLmsoxfA2aQxvk8b9PTvzr8OFLC44xq1f7uX/7TD4Xoc2TMvJYmi1S0YO36PHtHfCUtV7Z4wkAzZPAGtThvWXhCRhiQHNPbFbpdShcblNrn/4t40u19xeE02P91brHoPP5+wLJzarDCFag3Unipnx2dd0dCWyfHAvTq+ngXxDUp0OpnXMYlrHLL4tLee1guO8WnCMV/KP0T05katzsvifnCwcvhoW0+YnWB1j+Ups1ARVowyQRreiKVZ3hxyKI59/hgZ6du4e8W31HT0Ooxl3PQjRWjz33WE08PbgnqS3oFFst2QX/3d6DrO7Z7P+RAmLC47x5N5D/HFPAWeXek+sFR5rLwc0xX+cjIUeeWOSMqzOV6TRrQifylOnyN+wDq0U5/74RqvDEaJVKyiv5P2jJ7m+c7sWJSvVGUoxom0aj53Vla0j+vFYn664fW1DNh0rDss2IiX2Gt3Gzg9RL9+gvBaSGhbRIu7SUipPFrF2/sN8umsb2newiInusYWIYQ/vKSDJUNzSNTIDgvovGaX1cnPzRwcos3kNS+xdE4oxypCO40RsMj0eVv7iVj4/8C0ASkP3tDbk9OyF05lAuwHnWBugEK3YjpIyXs4/yj1ndiIzIbKH8UTfj49Kt70TFh1zjW6tDiBENqi5koRFNMumPz/J5/l76ZaRRaIzgVG33kFWv4bHCRJChM/9Xx+gS1JinduXIyHR6W05YP82LN5HG5xXWydleHvotZAkLKJZPlrjHQvj+08/h6OB25aFEOG3/kQx/z5SxIK+3XAZkW+GmOjwbqPS7rc1S8YSedLoVsSicROnALB72RKLIxEifmituW/3AQakJzO1Q5uobDPJn7DYvIal6te/JCwRoQywuOM4SVhEs5xz/U9JcpvsWvOh1aEIETf+dbiQT4pO8dszOmFEqSbB6bskVOm2eQ0LUsMSUUq65hc2YHo8lJ44QsnhA5QeOUhZ4XEqKkopryyloqKUiooy3O4K8LjRbg/a9KBLNV3aDsZdavDlX/5drbRaB4uGPt9Kg4KEIieOEgdlHctDirdH+kBwh7yrQsSsSlPzwNcHuDArnVFtG+7NNtySfQnLU8u38+wHu5pcXjXwot40QvkfGkgymlofAj3yZphFrAU6fDKPHV89G1qcELjDsfY80yylHSdwqcomywxWCh4KKvI48E7fBpfRjbyqu2xwiUSd5YLJ7fyrmJV8l2XtiN2SsITBt1/+ly//3204S70DiQU+Er4vgK79oaj2xdC+IbvLKk6RgBOHVjg0GBqUCYbWGLVr4Rr9zHm/+lV3zGvQvo+p79HQGmelJsGtSXBDgqfuPjl9f/UNW+gxHLjG/JLkdj1wmxWws+b9+fU9qz7FG5/3IOg0ErxR70ios2xjo8me1+5ijNKMBucL0dr848ARvimt4G/9ozuWWI/MZM4f3JGjJfUPlFj1o7vuabO+H+S61ozqi9RcvlZ5uu7yNdbR7XjB+QO6Z5ZiOOpePGjqlF/9sfqy+8sq6GN8x+mJwf+oakphUjKl7dJIMVKqJtZ3uNOqWlJX34J1V6o/+aue+alGlm0wLaTQOEqRQxrdxjSPx81X/3cLGYdLOHZOd5Su+sCrwHeg+pdTo3TNL60CtJmBSkzB4UzENMBjKLRSaEOhDaPu56jWaxPv4F8ajak1Go2BwjAcKBSGMlDK92g4IDEBXIkoVyIq0YUzMxNn1mkkntYOV2Zbkl1ppLjSSPI9ulwpOBxOPMB7Ty+iz4Eu7DrrCGNnfj/s72lTzHIPB363ljbZnaK+bSGscNLt4U/fHOTqnCzOSovu+GGGYfDq/5wb1W0236iwl5j74X+5vf1hzu1/aVjLbRvW0iJv1+6H4Ou3LI1BEpYW+uDx/0fX3ScpfuRXXHbJ9VaHE1Fut5uPF7xJ/wPd+G74KcZOjX6yIkQ8ejn/KMUeD786PcfqUOJSDI2O0qpJo9sW+G7nFk57/m12jTuT81p5sgLwwZtvceb+jmzve5BhUydZHY4QceNQhZtOrgQ6J0kXAtGm0EG3ERGRJQlLMOpJr03T5PNfzqI02cGY+5tu4NUapH3tvQ41etoUiyMRIr5UmprEKPS5IupSkq7YhnwDgqBNX0MjVfV2rfrz3XT76gSOX88iM6ujRZFFV3FmOd+lHibRZW1LcSHiyUm3h0+KSkiWhMUykrDYg3wDguHr4VH5Wp7n7/mczGeWsHtEV4ZdMcvKyKLK4TZs1iWTHEZE6/b1qXIu2byD7SVlzOkRHz+M7EahpQ2LTUjCEgzTd9+v4cA0Tbb86mdUJihGPvgXa+OKMke5oqK+e6CFEGH34dEiJm/egQbeHdKLC7Ki1/eKqEnyFXsIKWFZsGABAwYMICMjg4yMDIYPH867774bmK+UqvfvoYcearDMhQsX1rtOWVlZ8/cqzLSvS2rlMPjo+fs5fesRPLN/QtsOXS2OLHqOfldAl6PtqMiVHFeISHt67yGu/exrhmSk8s7gXpyZkmR1SHHL15uWxVEICPG25i5duvDggw9y5plnAvDCCy8wdepUtmzZQr9+/cjPz6+x/LvvvstPfvITrrzyykbLzcjIYPv27TWmJSXZ6AvqG6PiSP7XpDz5Cl+f14lLfzjb4qCi6/NV6+lKJgMvGW11KDJUiGjV/nuimPt2H+Dmrh24s0dHHNLVvMW0xSPo2IjFH8WQEpYpU2reHXL//fezYMEC1q9fT79+/cjJqdlHwNKlSxk3bhw9evRotFylVJ117UR7vJdBvrjrDtIUDP1jfF0KAiguOYlJOu3adrA6FCFatdcPHue0BCd39egYtfGCRMMU0g+LXTS74ziPx8Nrr71GSUkJw4cPrzP/4MGDvP3227zwwgtNllVcXEy3bt3weDycc845/P73v2fQoEGNrlNeXk55eVVXyUVFRaHvRLB8jW477TjG4buuo13HxhOw1ijnQAZuw4PpMevt9loI0TzHKt38+0ghAF8Vl/H3A0e5O4qDG4rGKTRySQhbZG0hJyxbt25l+PDhlJWVkZaWxpIlS+jbt+4ATi+88ALp6elcccUVjZbXp08fFi5cyNlnn01RURGPPfYYI0eO5NNPP6Vnz54Nrjd37lzuvffeUMNvluJybzL09bk5XDr911HZpt0UnlZGaVE5vSVZESKsZnz2NZuKTgHeRoW/Pj2Hm7tKTaZ9WH+itgurU+iQE5bevXuTl5fHiRMneOONN5g5cyarV6+uk7T87W9/49prr22yLcqwYcMYNmxY4PXIkSM599xzeeKJJ3j88ccbXG/OnDnMnl3VjqSoqIjc3NxQdycoO1NOcqAtjHnwqYiUHwuMJCcpR2w2koMcR0SM01qzqegU52aksGxQTzxoXNLfiq0okDYsNhHyGSgxMTHQ6HbIkCFs3LiRxx57jGeeeSawzEcffcT27dtZvHhxyAEZhsF5553Hzp07G13O5XLhilIHZiVn5LBwkoOfdewele3ZkTKhwhG+4dWFELCvzDsC8u3dsnEaCqflv2FFbQotP45sosWpvNa6RlsSgOeee47BgwczcODAZpWXl5dHx4726STJrd0AJBgJFkdinaQjisL0UqvDEKJV+bbUm7CckSK9R9uZdM5vDyHVsNx5551MnjyZ3NxcTp48yaJFi1i1ahXLly8PLFNUVMRrr73Gn/70p3rLmDFjBp07d2bu3LkA3HvvvQwbNoyePXtSVFTE448/Tl5eHk89ZZ/LL27Tm7A4jchfEpk7dy5vvvkmX331FcnJyYwYMYJ58+bRu3fviG+7tqOHD5K3dDUl5SWcW3wmnnNTox6DEK2VqTX/PHwC8Na0nCF9rdiSjCVkHyGdgQ8ePMj06dPJz88nMzOTAQMGsHz5ciZMmBBYZtGiRWitueaaa+otY+/evRjVrtGeOHGCG2+8kYKCAjIzMxk0aBBr1qzh/PPPb+YuhZ/bdGNgoKLQan/16tXcfPPNnHfeebjdbu666y4mTpzItm3bSE2NbsKw7pV3OOfAmRxJPMGuMw4xZuL3o7r9xhxXxZw8/B2Ju08Gpulqrdh1PS3aa3dOaBhGvZ0WpqamkpmZGZX9EPFpb2k5kzfv5Gilm96pSZyeLDUsdqWw5orQggULWLBgAd988w0A/fr147e//S2TJ0+2IBo/ay9ZKl3fkT0GFRUVkZmZSWFhIRkZGWEt+6UvX+JPm/7EJ9M/CWu5wTh8+DAdOnRg9erVjBkzJmrb/fDtf9LzozZs7bmPyT/5YdS2G4yKU+XMnfcgWkXmo+twOJgzZw5Op80aGYtWYfepMi7dvJMit4fbumXzaxuPEWTPk2Z09f5wNdPanOC+QVOjut1//vOfOByOGh21PvTQQ4GOWqNt164/8uE3y/jpRR+Hvexgz99yRA6C23RjKGta7hcWevtnyMrKito2TY9J9roEdmXnM+n6H0Rtu8EyTROtNOPPHkX/CwfXqfmq/rr6c6114M80zRqv/dN27drF+++/j8fjiVjCYpompmmyb98+1q5di8PhoEOHDlx44YUR2Z6IvEpT41Q1P28erdlRUsaB8ko+On6STKeDbcVlgctAX43qT5sEex+Cm+rdPB54a1ii/7u+qY5a45G9vy028fznz1PuKW96wTDTWjN79mxGjRpF//79o7bdfd9+TYY7leLhKTUu3wUjmm1wUlzJtG3bNqxlHj16FPBe2jQMo06CU99j9b9gptXWoUMHduzYIQlLDPqyuJQ/7zvM0kPHaeN0MrVDG85IcbG+sIQPjhZxwl1zsNCz05KZlduBkW3TbJ+sgJw0wd+GxdpLIU111Bov7P+NsYGB7Qfywb4Por7dW265hc8++4yPPw5/FVxDDhbs5+vVn9KTDqQkpIS8vp3a4DRHbm4uZ599Nh5P1YmmenuX6o+1nzc2raHp7dq1Y//+/TUGERX25tGa9SeK+bKkjAe/zkcB52emku1KYHHBMU64PXR2JfCjTqfR0ZVAjiuBC9qmk+qITju4SInHk+bH+Xkcpw1QaMn2g+2oNTqsbz0iCUsQzm5/Nv8t+G9Ut3nrrbeybNky1qxZQ5cuXSK2Ha01W/67luN7DmKerOCs3Z3pSQc+z/2WCwdeHXJ51e8YA3j++efp0KEDmzdvjmobnObKzMxscrDOcNu/f39Utyda5uE9BTz67UEAJpyWwZ/7diPV6QC8d/7sKS2nW5ILpxG7yUl19jppRtemoweATlzTvfGhYiIl2I5a44UkLDajtebWW29lyZIlrFq1itNPPz2i21v11zfouTub0zgNBwY7u+XT7eJzmNR9VFh+DVrRBkeISCjzmHRf8xkA/9ulPdd3aUf3Wnf3GEq1utuT4/mk6UHjpJJ+bbtasv1gOmqNJ5Kw2MzNN9/Myy+/zNKlS0lPT6egoADw/vJPTk4O67Y+Wfcfeu7O5qshhxk0YTSVxeWM7RSeRAUi1wYnhmvVRQz70zfe72Jbp4PfnRk/gxPG80nT1BrDRh3z19dRazyRhMVmFixYAMDYsWNrTH/++ee57rrrwrqtI1v3kujM5MIrLvc2rg1z1yNWtMERIty+K6vgvt0HWHboBABLz+0ZN8lKfeLppOnR2jdac/QF01FrvJGExWai2S1OVkEKSWZiRBoCRqsNjhCRUuL28O6RQn67az8JSvHkWV25tH0bkuNoxPJ4P2l6LKxhCaaj1ngjCUucOny4gJxTWXx97gnODGPCEtU2ONY3WhetkEdrHErx86/28vbhQnKTEnlncE/aJ8bfWGLxftL0JizWHGiee+45S7ZrZ5KwxKnD+w+QASRlhPdW42i2wYk0O43rJCLvaIWb+3YfYOmh43R0JbCntII7umXzf6fn4IjTS0DxftK0soZF1BU/dZuihm8/2Eq5quD088Pb+dOCBQsoLCxk7NixdOzYMfC3ePHisG4nGvx9yqxfv56VK1fidruZOHEiJSUlVocmImBxwTEWFxwjw+mgb1oyz/Xvzq/iOFkR4NEmDqnKtQ2pYYlDn27ewNmHevBFn/1MysoOa9mtZGgqIPb7lBGhKTdN2ic6+Wxk9HqVFvbm0UgNi41IwhKHjqz5GpWQwYU/vMLqUJrJml+80qdM6+bR4LC4C3ZhLyYmRoQGWRWhk0tCcWbblk/ofbALRwe5SUhMtDqcmGHVuE4ieryNba2OQtiJaWGjW7uxYgDI2qSGJY4cP3aU8re+43ACDL14vNXhtFg0vz7Sp0zrpyGu+1cRdVl5l5CoS2pY4sR7/3idkj9uI9mdROaP+5CSkmZ1SDHD36fMhx9+GJE+ZRwOB6Zpsm7dOtxud9jLF0I0jyQs9iI1LHFg5xef0+eLbApOO0HOD/rTJTey4xO1FtHqU6Z///589913rFixgg0bNnDhhRfSv39/b+/DImrktCRq82hoJWNYhoXVo43LETFIdrh+11wHDu4DoMO0vpKshODmm2/mxRdf5OWXXw70KVNQUEBpaWlYt5OYmMj3vvc9Zs2aRU5ODm+++SbPPvssu3fvDut2RNPk3CSqkzYs9iIJSxBUjB/GOrbzXsY4eaLQ4khiS7T7lGnfvj0/+MEP+PGPf0xCQgL/+Mc/OHr0aES2JYRomgekHxYbkYQlDpSf8tYIpLRJtziS2KK1rvcv3INQ1ta1a1euvvpqAI4cORLRbYkqrakPIREeHq3ltmYbkYQlDlQUexMWV1JsdY3fEP/lOben9TZQTU1NxTCMQN8vQojoM1FySchGJGGJAyk5mQDs277T4kjCw38nza6CPRZHEjmGYZCRkSEJSxRppA2LqEkSFnuRhCUOlLnLAPAUV1gcSXg4HA4AupzWyeJIIiszM1MSFiEsZGpJWPwOHHiVsrICS2OQhKWVO1p0BOfrx9iXcYgh4y6wOpyw8N/um+ZKsTiSyMrNzWX79u2cOHHC6lCEiEsmhowl5GMYCVaHIAlLa/fNNztp606n/ZTeJCYlWR1OWFjdF0C0jB49mqSkJN59912rQ4kLGoiTj5YIklwSqpKTczlJSTmWxiAJSyt38jvvbbHJaa2vZ9tY7hsnGC6Xi4svvpjt27ezfft2q8MRIu6YGBhKalgAsMFddJKwtGJaa/SmQo44T9A+x9rMWDRP3759OfPMM3nnnXeoqGgdbZCEiBVSw1Kb9HQrIqRg3z56nurKwaEVJCa3jstB8UYpxSWXXEJJSQlr1qyxOpxWTe4SErV5ExapYbELSVhasZ3vbAKg37lDLI4kvAJtWOLkh09WVhajR49m7dq1HDp0yOpwhIgbWitUvBxoYoAkLK1YwmGT7W320qVzN6tDiYh4OoyMHDmStm3b8vbbb0uPrBEib6uozVAaLfVu1cglIREBH779T3JLskkZ3MHqUEQYOJ1OLr30Ur799ls+/fRTq8NptWJ93DARXgokYbGRkBKWBQsWMGDAADIyMsjIyGD48OE1brlUStX799BDDzVa7htvvEHfvn1xuVz07duXJUuWNG9vBFprvtiymZ4ftWF79ncMHT/e6pAiJ85+Evfo0YP+/fuzYsUKTp06ZXU4QrR6BhpTEhbAHndlhpSwdOnShQcffJBNmzaxadMmLrzwQqZOncoXX3wBQH5+fo2/v/3tbyiluPLKKxssc926dUybNo3p06fz6aefMn36dK6++mo2bNjQsj2LU59//gmZi70nszYjugY6WROtw6RJk/B4PLz//vtWh9Lq2OGALOzFUBpTS8JiFyGdzaZMmcIll1xCr1696NWrF/fffz9paWmsX78egJycnBp/S5cuZdy4cfTo0aPBMufPn8+ECROYM2cOffr0Yc6cOYwfP5758+e3aMfi1fHtBwDYd0EpAwafb3E0kREvHcfVJz09nfHjx7N582YKCqztJrs1it9PlqiPQtqw2ImzuSt6PB5ee+01SkpKGD58eJ35Bw8e5O233+aFF15otJx169Zxxx131Jg2adKkJhOW8vJyysvLA6+LioqCD74ZTlWe4vKllze/gCZ+vFX/dRd4rquea3Sdxpb1LXfNjvGcTGkDmxX//uQFQNXsvVNVPanxi1L5/uOfX2dIdVXjaB740aFqru6fUKfs6kEE8f2v/Wu3etsC0zQpSC7gpd2v8+pTy+ptd1B9/drzG5tXfX5D7Rmamp/lyuLykZeTkJDQYAPZ+qYHOy01NRWn08natWu54oor6i1fNM/u0nKe3nsIA3A5DFxK4TIULsMgyWGQZFT9m2vt/Vp7/3St175+kPzLAqbvtW5gXWqt66eU95NW42usvJ8//3Sl/O0twNRgor2PWmNWm6Y1mIAnMF0HYjOrzQtMq7Wup9Y009SYmHi0xq09mNr0leXxbktrPJiYGsA/T/vi865LYNsm2j/PNAPvg+lbX/vW1zXiMwPHxsAx0v+catMArc3A++1fhhrr4ptrBpY5XllGtj7An/99D0oZKBygDJwOF21dWQB4tIlHuzG1icf0vQfVboVW/v8pcDmSSE9MJz0xg/TENiQnZpLgTEMph/9fEpTvX1YpavwrVzuG1vhEVF9OGb75BkoZNcvD8D03qm3D8K1r+A7xtZbzla8wKCvb38C3JnpCTli2bt3K8OHDKSsrIy0tjSVLltC3b986y73wwgukp6c3eUAtKCggOzu7xrTs7Owmfz3OnTuXe++9N9Twm2Vc13HsKdxT40NYQwjJSL3ztfYdlPwfbP8HzMtfo6Coml67lsG/3qHECgYk9KJrWtfAAaxGjNUmqOpVnbpqpveLq2qurKvWVVULUeOp1lVxV9/lamUrrape1jrfV+1nPWpNbHuoM2XtFEaio76lLfWf7f/hsWWPRXYjCVB8qJjs/dlNLyuC4iwtIrX8CI9/+Tmm1rg1VGp/ctp6fmkrwPAnPMpbze4/Pflfo8Dwn75U1TwVWEYF1lNKYSgDQxm+EyUYyuHbhu+171F5n/mWMWoc9wzl/VMoEpQRSMoM5fBuz9cm0vBvE8O3bX/8RqDdJIH9MQJlB46dhq8MXywY/tO0QilHYP8UCo+7kL5s5bykG9HajdYetHZTVnmS46UFoAwcyoFDOXEYDgzlwGkkYPgSB+1LtLwJkUmZu4Si8kKOnDrEnsKvKXOfwmOWgTZ9y1dPean1vHoiW3t61TTvMpHpO6Z7234RKTdYSod4j2RFRQV79+7lxIkTvPHGG/z1r39l9erVdZKWPn36MGHCBJ544olGy0tMTOSFF17gmmuuCUx76aWX+MlPfkJZWVmD69VXw5Kbm0thYSEZGRmh7JIQYeV2uykpKal3XkOXs+qb3tSyiYmJJCRYPyBZa2ZqTbmpKTPNwCNUq4ikZg1IVW1H7doPVaMmRDWwLrXWrV4LU/13Q/UanOq1NoYv4fAnGYbvhO494fuSkzi+pBpP/MmP1ia+ujdfYmNWm1Y1v+Y0/6fO9GVD3mmJiVk4HMlhj7WoqCgwOn1j5++Qa1gSExM588wzARgyZAgbN27kscce45lnngks89FHH7F9+3YWL17cZHk5OTl1alMOHTpUp9alNpfLhcvlCjV8ISLO6XSSmZlpdRgiDAylSHYokh3SeF3EFn9Nk1Kt57Pb4j3RWteo6QB47rnnGDx4MAMHDmxy/eHDh7Ny5coa01asWMGIESNaGpoQQgghWomQaljuvPNOJk+eTG5uLidPnmTRokWsWrWK5cuXB5YpKiritdde409/+lO9ZcyYMYPOnTszd+5cAG677TbGjBnDvHnzmDp1KkuXLuW9997j448/bsFuCSGEEKI1CSlhOXjwINOnTyc/P5/MzEwGDBjA8uXLmTBhQmCZRYsWobWu0Salur1799boG2TEiBEsWrSI3/zmN9x9992cccYZLF68mKFDhzZzl4QQQgjR2oTc6Naugm20I4QQQgj7CPb83Xpa4wghhBCi1ZKERQghhBC2JwmLEEIIIWxPEhYhhBBC2J4kLEIIIYSwPUlYhBBCCGF7krAIIYQQwvYkYRFCCCGE7UnCIoQQQgjbC3m0Zrvyd9hbVFRkcSRCCCGECJb/vN1Ux/utJmE5efIkALm5uRZHIoQQQohQnTx5kszMzAbnt5qxhEzT5MCBA6Snp6OUith2ioqKyM3NZd++fXE5ZlG87z/IeyD7L/sfz/sP8h6Ee/+11pw8eZJOnTrVGBy5tlZTw2IYBl26dIna9jIyMuLyg+oX7/sP8h7I/sv+x/P+g7wH4dz/xmpW/KTRrRBCCCFsTxIWIYQQQtieJCwhcrlc/O53v8PlclkdiiXiff9B3gPZf9n/eN5/kPfAqv1vNY1uhRBCCNF6SQ2LEEIIIWxPEhYhhBBC2J4kLEIIIYSwPUlYhBBCCGF7krA04v7772fEiBGkpKTQpk2bepfZu3cvU6ZMITU1lXbt2vHzn/+cioqKGsu8+uqrnHPOOaSkpNCtWzceeuihKETfcuHa/3//+98MGzaM9PR02rdvz5VXXsmePXuisActE479v+eee1BK1flLTU2N0l40X7j+/bXWPPzww/Tq1QuXy0Vubi4PPPBAFPagZcKx/9988029//7Lly+P0l60TLg+A367du0iPT29wbLsJhz7v337dsaNG0d2djZJSUn06NGD3/zmN1RWVkZpL5ovHPu/atUqpk6dSseOHUlNTeWcc87hpZdealY8raan20ioqKjgf/7nfxg+fDjPPfdcnfkej4dLL72U9u3b8/HHH3P06FFmzpyJ1ponnngCgHfffZdrr72WJ554gokTJ/Lll19yww03kJyczC233BLtXQpJOPb/66+/ZurUqcyePZuXXnqJwsJC7rjjDq644gq2bNkS7V0KSTj2///+7/+46aabaqw3fvx4zjvvvKjsQ0uEY/8BbrvtNlasWMHDDz/M2WefTWFhIUeOHInmrjRLuPYf4L333qNfv36B11lZWRGPPxzC+R5UVlZyzTXXMHr0aNauXRutXWiRcOx/QkICM2bM4Nxzz6VNmzZ8+umn/PSnP8U0Tdsn7uHY/7Vr1zJgwAB+/etfk52dzdtvv82MGTPIyMhgypQpoQWkRZOef/55nZmZWWf6O++8ow3D0Pv37w9Me+WVV7TL5dKFhYVaa62vueYafdVVV9VY79FHH9VdunTRpmlGNO5wacn+v/baa9rpdGqPxxNYZtmyZVoppSsqKiIeezi0ZP9ry8vL04Bes2ZNpMINu5bs/7Zt27TT6dRfffVVtMINu5bs/549ezSgt2zZEqVoIyMc34Ff/epX+kc/+lGDZdlZOI8BWmt9xx136FGjRkUi1IgI9/5fcskl+vrrrw85Drkk1ALr1q2jf//+dOrUKTBt0qRJlJeXs3nzZgDKy8tJSkqqsV5ycjLfffcd3377bVTjDbdg9n/IkCE4HA6ef/55PB4PhYWF/OMf/2DixIkkJCRYFXpYBLP/tf31r3+lV69ejB49OlphRkww+//Pf/6THj168K9//YvTTz+d7t27c8MNN3Ds2DGrwg6bUP79v/e979GhQwdGjhzJ66+/Hu1QIybY9+CDDz7gtdde46mnnrIizIhpzjFg165dLF++nAsuuCBaYUZMc/YfoLCwsFm1jJKwtEBBQQHZ2dk1prVt25bExEQKCgoA7z/em2++yfvvv49pmuzYsYP58+cDkJ+fH+2QwyqY/e/evTsrVqzgzjvvxOVy0aZNG7777jsWLVpkRchhFcz+V1deXs5LL73ET37yk2iFGFHB7P/XX3/Nt99+y2uvvcbf//53Fi5cyObNm7nqqqusCDmsgtn/tLQ0HnnkEV5//XXeeecdxo8fz7Rp03jxxRetCDnsgnkPjh49ynXXXcfChQtb3UCBoRwDRowYQVJSEj179mT06NHcd9990Qw1IkI9BgK8/vrrbNy4keuvvz7k7cVdwtJQI8jqf5s2bQq6PKVUnWla68D0n/70p9xyyy1cdtllJCYmMmzYMH7wgx8A4HA4wrNTIYj2/hcUFHDDDTcwc+ZMNm7cyOrVq0lMTOSqq65CW9DJcrT3v7o333yTkydPMmPGjBbtQ0tEe/9N06S8vJy///3vjB49mrFjx/Lcc8/x4Ycfsn379rDtV7Civf/t2rXjjjvu4Pzzz2fIkCHcd999zJo1iz/+8Y9h26dQWXEM/OEPf8iYMWPCtg8tYdUxYPHixXzyySe8/PLLvP322zz88MMt3pfmsPIYuGrVKq677jr+8pe/1GjTFay4a3R7yy23BBKGhnTv3j2osnJyctiwYUONacePH6eysjKQdSqlmDdvHg888AAFBQW0b9+e999/P6TthFO09/+pp54iIyOjxgH6xRdfJDc3lw0bNjBs2LDQdqCFor3/1f31r3/lsssuIycnJ+h4wy3a+9+xY0ecTie9evUKLHPWWWcB3rsLevfuHUL0LWflv7/fsGHD+Otf/xrUNiIh2u/BBx98wLJlywInaK01pmnidDp59tln+fGPfxz6TrSAVZ+B3NxcAPr27YvH4+HGG2/kF7/4RdR/uFq1/6tXr2bKlCk88sgjzf7RFncJS7t27WjXrl1Yyho+fDj3338/+fn5dOzYEYAVK1bgcrkYPHhwjWUdDgedO3cG4JVXXmH48OF06NAhLHGEItr7f+rUqTpfSP9r0zTDEkcorPr337NnDx9++CHLli0Ly7abK9r7P3LkSNxuN7t37+aMM84AYMeOHQB069YtLHGEwqp//+q2bNkSWN4K0X4P1q1bh8fjCayzdOlS5s2bx9q1awPHxGiyw2dAa01lZaUltcxW7P+qVau47LLLmDdvHjfeeGPzNxhyM9048u233+otW7boe++9V6elpektW7boLVu26JMnT2qttXa73bp///56/Pjx+pNPPtHvvfee7tKli77lllsCZRw+fFgvWLBAf/nll3rLli365z//uU5KStIbNmywareCFo79f//997VSSt977716x44devPmzXrSpEm6W7du+tSpU1btWlDCsf9+v/nNb3SnTp202+2O9m40Wzj23+Px6HPPPVePGTNGf/LJJ3rTpk166NChesKECVbtVtDCsf8LFy7UL730kt62bZv+6quv9EMPPaQTEhL0I488YtVuhSSc3wG/WLpLKBz7/+KLL+rFixfrbdu26d27d+tXX31Vd+7cWV977bVW7VbQwrH/H374oU5JSdFz5szR+fn5gb+jR4+GHI8kLI2YOXOmBur8ffjhh4Flvv32W33ppZfq5ORknZWVpW+55RZdVlYWmH/48GE9bNgwnZqaqlNSUvT48eP1+vXrLdib0IVj/7X23uY2aNAgnZqaqtu3b6+/973v6S+//DLKexO6cO2/x+PRXbp00XfeeWeU96BlwrX/+/fv11dccYVOS0vT2dnZ+rrrrmvWwSrawrH/Cxcu1GeddZZOSUnR6enpevDgwfof//iHBXvTPOH6DFQXSwlLOPZ/0aJF+txzz9VpaWk6NTVV9+3bVz/wwAO6tLTUgj0KTTj2v6EyLrjggpDjUVpbUCclhBBCCBGCuLtLSAghhBCxRxIWIYQQQtieJCxCCCGEsD1JWIQQQghhe5KwCCGEEML2JGERQgghhO1JwiKEEEII25OERQghhBC2JwmLEEIIIWxPEhYhhBBC2J4kLEIIIYSwPUlYhBBCCGF7/x8SyPGYYdAgfAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#1/4/24 -- below works for states without sliced-out districts.  Will not work for Florida panhandle\n",
    "\n",
    "aDP = float(statePop)/nDistricts\n",
    "maxCCBratio = 1./8.  #adjustable max fraction of district pop for corner county blocks.  Let's try 3/16\n",
    "maxCCBpop = maxCCBratio * aDP\n",
    "print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "CCBlist, CCBpop, passThruList = list(), list(), list()  #\"waiveThru\" counties get chance to join a cluster even if high pop\n",
    "nFuses = 0\n",
    "for c in has1neighborCs:\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and only 1 neighbor is less pop than\",int(maxCCBpop),\"vs districtPop\",int(aDP) )\n",
    "    if countyPop[c] > maxCCBpop:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        nc = neighborCountyList[c][0]\n",
    "        plotPoly(countyGeom[nc],0.5)\n",
    "        plotPoly(MAP,0.2)\n",
    "        print(\"county\",c,\"has pop\",countyPop[c],\"and its only neighbor has pop\",countyPop[nc],\"vs districtPop\",aDP,\". Default = keep un-fused\")\n",
    "        print(\"enter 0 to keep\",c,\"as an unfused collection of units, 1 to fuse as one unit and stop, 2 to force-add at least the next closest county\")\n",
    "        fuseChoice = input(\"0, 1, or 2.  Any other input taken as a zero\")\n",
    "        if fuseChoice == 0:\n",
    "            keepUnfused = True\n",
    "            break\n",
    "        elif int(fuseChoice) == 1:\n",
    "            CCBlist.append([c])\n",
    "            CCBpop.append(countyPop[c])  \n",
    "            hasFewNeighborCs.append(c)  #this adds this [c] to the final list of fused units, but will fail to find more in below\n",
    "        elif int(fuseChoice) == 2:\n",
    "            CCBlist.append([c,nc ] )\n",
    "            CCBpop.append(countyPop[c] + countyPop[nc])\n",
    "            hasFewNeighborCs.append(c)\n",
    "            passThruList.append(c)   #pass on thru to the below 2neighbor logic even if too high-pop to qualify\n",
    "    else:\n",
    "        hasFewNeighborCs.append(c)  #normal case; we'll handle in next, more general, for loop            \n",
    "        \n",
    "for c in hasFewNeighborCs:\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and 1 or 2 neighbors is less pop than\",int(maxCCBpop) )\n",
    "    if countyPop[c] < maxCCBpop :\n",
    "        CCBlist.append([c])\n",
    "        CCBpop.append(countyPop[c])\n",
    "        CCBno = CCBlist.index([c])\n",
    "    if c in passThruList:\n",
    "        CCBno = CCBlist.index([c,neighborCountyList[c][0] ])\n",
    "    if countyPop[c] < maxCCBpop or c in passThruList:            \n",
    "        CCBstarter = c\n",
    "        canAdd = True\n",
    "        while canAdd:\n",
    "            nbrSet = set()\n",
    "            for cc in CCBlist[CCBno]:\n",
    "                nbrSet = ( nbrSet.union(set(neighborCountyList[cc])) ).difference(set(CCBlist[CCBno]))\n",
    "            nPop = [countyPop[cc] for cc in nbrSet]\n",
    "            nDist = [countyGeom[cc].centroid.distance(countyGeom[CCBstarter].centroid) for cc in nbrSet]\n",
    "            idx = np.argsort(nDist)\n",
    "            nbrList, newList = list(nbrSet), list()\n",
    "            for i in range(len(nDist)):  #add counties, closest to starter that will fit until over\n",
    "                cc = nbrList[idx[i]]\n",
    "                if CCBpop[CCBno] + countyPop[cc] < maxCCBpop:\n",
    "                    newList.append(cc)\n",
    "                    CCBlist[CCBno].append(cc)\n",
    "                    CCBpop[CCBno] += countyPop[cc]\n",
    "                    #print(\"adding county\",cc,\"with pop\",countyPop[cc],\"to list started by\",CCBstarter,\".Cluster pop now\",CCBpop[CCBno]  )\n",
    "            if newList == list():  #no eligible neighbor counties found; stop\n",
    "                canAdd = False\n",
    "                for cc in CCBlist[CCBno]:\n",
    "                    plotPoly(countyGeom[cc])\n",
    "                    plotCenter(CCBno,countyGeom[cc])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "                    \n",
    "print(\"Below I plot these again by county no, with faded neighboring counties\")\n",
    "plotPoly(MAP,0.15)\n",
    "for L in CCBlist:\n",
    "    print(CCBlist.index(L),\" \",L)\n",
    "    for c in L:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        for cc in list(set(neighborCountyList[c]).difference(L) ):\n",
    "            plotPoly(countyGeom[cc],0.4)\n",
    "            plotCenter(cc,countyGeom[cc],8)\n",
    "plt.show()\n",
    "rejectList = list()\n",
    "print(\"Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are\",r3(aDP), int(maxCCBpop))\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if L[0] not in passThruList:  #if we forced the fused-counties list above, don't give option here to modify\n",
    "        print(\"let's decide whether to delete, accept, or modify list\",L,\"with pop\",CCBpop[i] )\n",
    "        isOK = input(\"enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list)\")\n",
    "        if not (isOK == 1 or isOK == str(1)) :\n",
    "            if isOK == 0 or isOK == str(0) :\n",
    "                rejectList.append(L)\n",
    "            else:\n",
    "                notGood = True\n",
    "                while notGood:       \n",
    "                    Lnew = ast.literal_eval(isOK)        \n",
    "                    if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                        notGood = False\n",
    "                    else:\n",
    "                        print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                        isOK = input(\"Try again here \")\n",
    "                print(\"OK, I will replace\",L,\"with\",Lnew)\n",
    "                CCBpop[i] = np.sum( [countyPop[c] for c in Lnew] )\n",
    "                CCBlist[i] = Lnew.copy()\n",
    "for L in rejectList:\n",
    "    del CCBlist[CCBlist.index(L)]\n",
    "    del CCBpop[ CCBlist.index(L)]\n",
    "stillAdding = True\n",
    "while stillAdding:\n",
    "    addMore = input(\"enter 1 if you want to manually add another corner-county cluster\")\n",
    "    if int(addMore) != 1:\n",
    "        stillAdding = False\n",
    "    else:\n",
    "        isOK = input(\"Type in a [county list], where the corner county is first in the list.  Or type 0 to stop\")\n",
    "        if isOK == 0 or isOK == str(0) :\n",
    "            print(\"OK, we'll stop adding corner clusters\")\n",
    "            stillAdding = False\n",
    "        else:\n",
    "            notGood = True\n",
    "            while notGood:       \n",
    "                Lnew = ast.literal_eval(isOK)        \n",
    "                if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                    notGood = False\n",
    "                    for L in CCBlist:\n",
    "                        if set(L).intersection(set(Lnew)) != set(list()) :\n",
    "                            notGood = True\n",
    "                            print(\"OOPS! The following inputted counties are already in\",L,\":\",set(L).intersection(set(Lnew)) )\n",
    "                            isOK = input(\"Try again here \")\n",
    "                    if notGood == False:\n",
    "                        CCBlist.append(Lnew)\n",
    "                        CCBpop.append( np.sum( [countyPop[c] for c in Lnew] ) )\n",
    "                else:\n",
    "                    print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                    isOK = input(\"Try again here \")\n",
    "print(\"Our final pops and fused-county lists are...\")\n",
    "allFusedCounties = list()\n",
    "CCBgeom = [dummyPoly for L in CCBlist ]\n",
    "CCBcp = list()\n",
    "for i, L in enumerate(CCBlist):\n",
    "    CCBcp.append( getHDcp([countyCP[c] for c in L], [countyPop[c] for c in L], [ j for j in range(len(L)) ] ) )\n",
    "    print(CCBpop[i],L)\n",
    "    pops, CPs = list(), list()\n",
    "    for c in L:\n",
    "        if c == L[0]:\n",
    "            CCBgeom[i] = countyGeom[c]\n",
    "        else:\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[c])\n",
    "        allFusedCounties.append(c)\n",
    "        pops += countyPop[c]       #  IS THIS EVEN USED?\n",
    "        CPs.append(countyCP[c])   #  IS THIS EVEN USED?\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(i,countyGeom[c])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "raw",
   "id": "d6dd5341-458c-4e5f-9eac-7f1082cb8164",
   "metadata": {},
   "source": [
    "for CO above:\n",
    "Our final pops and fused-county lists are...\n",
    "44650.0 [41, 52, 54]\n",
    "65547.0 [58, 48, 38, 61, 63, 32, 9, 31, 50]\n",
    "105949.0 [42, 17, 57, 56, 34, 3]\n",
    "42401.0 [4, 36, 45, 5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d97ebd69-96cd-4e26-9af1-848f2c5a339e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "20601a8c-c3a8-4247-b54b-ce5782450790",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing from above, develop corner county blocks from each low-pop corner county until it hits 0.125 of 721714\n",
      "now identify the border counties + border fused units, and interior small counties with pop < 7217\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#DO NOT RUN BELOW IF we are not fusing vtd's to larger units in this state. \n",
    "aDP = float(statePop)/nDistricts\n",
    "print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "\n",
    "borderList, borderType = list(), list()\n",
    "maxWholeBorderCountyPop = 0.01 * aDP   #to encourage contiguity, border counties > 0.01 aDP will be forced whole  #0.1\n",
    "maxInteriorBorderCountyPop = 0.01 * aDP\n",
    "print(\"now identify the border counties + border fused units, and interior small counties with pop <\", int(maxInteriorBorderCountyPop))\n",
    "borderVTDs, unitCounties, borderCounties = list(), list(), list()\n",
    "for c in range(nCounties):\n",
    "    if  countyGeom[c].intersects(MAP.exterior):\n",
    "        borderCounties.append(c)\n",
    "        if c not in allFusedCounties:\n",
    "            if countyPop[c] < maxWholeBorderCountyPop:\n",
    "                borderList.append(c+0.5)\n",
    "                unitCounties.append(c)\n",
    "                borderType.append(\"county\")\n",
    "            else:\n",
    "                for v in countyTractList[c]:\n",
    "                    if vtdGeom[v].intersects(MAP.exterior):\n",
    "                        borderList.append(v)\n",
    "                        borderVTDs.append(v)\n",
    "                        borderType.append(\"vtd\")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    borderList.append(i+0.25)\n",
    "    borderType.append(\"cluster\")\n",
    "    \n",
    "for i,b in enumerate(borderList):\n",
    "    if borderType[i] == \"vtd\":\n",
    "        plotPoly(vtdGeom[b])\n",
    "    if borderType[i] == \"county\":\n",
    "        plotPoly(countyGeom[int(b-0.5)],1.3)\n",
    "    if borderType[i] == \"cluster\":\n",
    "        j = int(b-0.25)\n",
    "        for c in CCBlist[j]:\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "            plotCenter(\"fused\",countyGeom[c], 6)\n",
    "      \n",
    "for c in range(nCounties):\n",
    "    if c not in unitCounties and c not in allFusedCounties and countyPop[c] < maxInteriorBorderCountyPop :\n",
    "        unitCounties.append(c)\n",
    "        plotPoly(countyGeom[c],0.4)\n",
    "        plotCenter(\"int\",countyGeom[c],8)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "71d771f8-dbe2-48f9-a702-9f66a62d1174",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now writing the master list of units, which may be individual vtd's, whole counties, or corner county clusters\n",
      "After surround checks, we appear to have 2824 building blocks defined.\n",
      "Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "working on unit neighbor lists for county 0\n",
      "I handled a surrounded vtd 2214 surrounded by vtd-unit 354 217 in county 16\n",
      "I handled a surrounded vtd 2215 surrounded by vtd-unit 479 342 in county 16\n",
      "I handled a surrounded vtd 2217 surrounded by vtd-unit 363 226 in county 16\n",
      "working on unit neighbor lists for county 20\n",
      "I handled a surrounded vtd 240 surrounded by vtd-unit 239 119 in county 26\n",
      "I handled a surrounded vtd 241 surrounded by vtd-unit 239 119 in county 26\n",
      "working on unit neighbor lists for county 40\n",
      "working on unit neighbor lists for county 60\n",
      "Whew, we now have a set of 2824  units (vtds,counties, clusters) and their neighbors to map onto polygonal Home Districts\n",
      "We resolved 5 VTDs that were surrounded by another VTD\n"
     ]
    }
   ],
   "source": [
    "#1/24/24 - modified this to never include surrounded VTDs as units.\n",
    "unitPop, unitCP, unitGeom, allUnits = list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#NOTE, WE DON'T ELIMINATE surroundees, we just disconnect them in neighborlists and xfer pops and geometries\n",
    "print(\"Now writing the master list of units, which may be individual vtd's, whole counties, or corner county clusters\")\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(countyGeom[c])\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "    if c in borderCounties:\n",
    "        borderUnits.append(len(allUnits)-1)\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "for v in range(nVTDs):\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for vv in set(countyTractList[c]).difference({v}) :\n",
    "            if nVTDneighbors[v] > 1:  #as long as we find two, kick out.  Will do full neighbor list later\n",
    "                break\n",
    "            if vtdGeom[vv].intersects(vtdGeom[v]):\n",
    "                nVTDneighbors[v] +=1\n",
    "                lastVTDneighbor[v] = vv\n",
    "        if nVTDneighbors[v] < 2:\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if vtdGeom[v].intersects(countyGeom[cc]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    break  #any vtd that touches a county line can't be surrounded\n",
    "for v in range(nVTDs):\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties:    \n",
    "        if nVTDneighbors[v] > 1:\n",
    "            unitCP.append(tractCP[v])\n",
    "            unitPop.append(tractPop[v])\n",
    "            unitGeom.append(vtdGeom[v])\n",
    "            vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "            allUnits.append(v)\n",
    "for v in range(nVTDs):\n",
    "    if nVTDneighbors[v] == 1:\n",
    "        uu = allUnits.index(lastVTDneighbor[v])\n",
    "        unitPop[uu] += tractPop[v]\n",
    "\n",
    "for i, L in enumerate(CCBlist):\n",
    "    unitCP.append( CCBcp[i] )\n",
    "    unitPop.append(CCBpop[i])\n",
    "    unitGeom.append(CCBgeom[i])\n",
    "    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "    borderUnits.append(len(allUnits)-1)  #all clusters are on the border\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined.\")\n",
    "print(\"Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for vv in list(set(vtdUnits).intersection(set(countyTractList[cc]) ) ):\n",
    "                            if countyGeom[c].intersects(vtdGeom[vv]):\n",
    "                                unitNbrs[u].append(allUnits.index(vv))\n",
    "                                unitNbrs[allUnits.index(vv)].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:\n",
    "            for v in countyTractList[c]:\n",
    "                if v in allUnits:  #remember, we didn't add surrounded units to the list; skip them\n",
    "                    u = allUnits.index(v)\n",
    "                    for vv in list( (set(vtdUnits).intersection(set(countyTractList[c])) ).difference(set([v])) ):\n",
    "                        if vtdGeom[v].intersects(vtdGeom[vv]):\n",
    "                            unitNbrs[u].append(allUnits.index(vv) )  #will catch complement later in this county's loop\n",
    "                    for cc in neighborCountyList[c]:\n",
    "                        if cc not in allFusedCounties:\n",
    "                            if cc not in unitCounties:                            \n",
    "                                for vv in list(set(countyTractList[cc]).intersection(set(vtdUnits)) ):\n",
    "                                    if vtdGeom[v].intersects(vtdGeom[vv]):\n",
    "                                        unitNbrs[u].append(allUnits.index(vv) )\n",
    "                                        unitNbrs[allUnits.index(vv)].append(u)\n",
    "            #nLength = [len(unitNbrs[allUnits.index(v)]) for v in countyTractList[c] ]\n",
    "\n",
    "            for v in countyTractList[c]:\n",
    "                if nVTDneighbors[v] == 1:  #surrounded unit. Already handled above\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    surrounder = allUnits.index(vv)  #unitNbrs[u][0]\n",
    "                    print(\"I handled a surrounded vtd\",v,\"surrounded by vtd-unit\",vv,surrounder,\"in county\",c)\n",
    "                    #plotPoly(vtdGeom[v])\n",
    "                    #plotPoly(vtdGeom[vv])\n",
    "                    #plotCenter(uu,vtdGeom[vv])\n",
    "                    #plotCenter(u,vtdGeom[v],6)\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(surrounder)\n",
    "                    #unitPop[surrounder] += unitPop[u]  #already taken care of in a previous loop\n",
    "                    #unitPop[u] = 0\n",
    "                    unitGeom[surrounder] = unitGeom[surrounder].union(vtdGeom[v])\n",
    "                    unitCP[surrounder] = unitGeom[surrounder].centroid\n",
    "                    #del unitNbrs[surrounder][unitNbrs[surrounder].index(u)]\n",
    "                    #unitNbrs[u] = list()\n",
    "                    #unitCP[u] = Point(-888, -888)\n",
    "                    #unitGeom[u] = unitCP[u].buffer(0.0001)\n",
    "                else:\n",
    "                    u = allUnits.index(v)\n",
    "                    countyUnitList[c].append(u)\n",
    "                    if v in borderVTDs:\n",
    "                        borderUnits.append(u)                    \n",
    "                    for i,geo in enumerate(CCBgeom):\n",
    "                        if geo.intersects(vtdGeom[v]):\n",
    "                            unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                            unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "            #if np.min(nLength) == 1:  #at least one surround in this county\n",
    "            #    plotPoly(countyGeom[c])\n",
    "            #    plt.show()\n",
    "\n",
    "CCBunits = CCBlist.copy()                        \n",
    "for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "    for ii in range(i+1,len(CCBgeom) ) :\n",
    "        if geo.intersects(CCBgeom[ii]):\n",
    "            unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "            unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"Whew, we now have a set of\",nUnits,\" units (vtds,counties, clusters) and their neighbors to map onto polygonal Home Districts\")\n",
    "print(\"We resolved\",len(surroundedVTDs),\"VTDs that were surrounded by another VTD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5acda29e-28a9-474b-9706-20a79121a07e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the original HD polygon shape assignment csv, e.g. ./2024state_HD_output/CO3108convexHD28nW4.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv ./2024state_HD_output/CO3108convexHD28nW4.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have read back in the original HD shapes\n",
      "County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\n",
      "Ready to capture unit centroids based on these HD poly shapes; see next block\n"
     ]
    }
   ],
   "source": [
    "#OPTION 1 - we already have an ensemble of HDpoly's and their weights\n",
    "#read them in\n",
    "#determine each cluster's required area fraction capture to get 1.00 cluster use across the HD set\n",
    "#then determine total pop (including cluster in/out) for each HD, and total unit use\n",
    "#then move into triage\n",
    "infilename = input(\"enter the original HD polygon shape assignment csv, \"+ \n",
    "                   \"e.g. ./2024state_HD_output/CO3108convexHD28nW4.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv\")\n",
    "shapeDF = pd.read_csv(infilename)\n",
    "HDvPop = shapeDF[\"HD-pop\"].to_list()\n",
    "HDweight = shapeDF['HDweight'].to_list() #shapeDF['HDwt'].to_list() or #shapeDF['HDweight'].to_list()\n",
    "HDarea = shapeDF['HDarea'].to_list()\n",
    "#tractPop = shapeDF['tractPop'].to_list()   #we will use vtd-mapped pops instead\n",
    "nHDs = len(shapeDF)\n",
    "hdCPx = shapeDF['centroid x'].to_list()   #note: these may be translated from outcroppings into a convex representation of the map\n",
    "hdCPy = shapeDF['centroid y'].to_list()\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs) ]\n",
    "HDradius0 = shapeDF['HDradius0'].to_list()\n",
    "HDradius1 = shapeDF['HDradius1'].to_list()\n",
    "HDradius2 = shapeDF['HDradius2'].to_list()\n",
    "HDradius3 = shapeDF['HDradius3'].to_list()\n",
    "HDangle0 = shapeDF['HDangle0'].to_list()\n",
    "HDangle1 = shapeDF['HDangle1'].to_list()\n",
    "HDangle2 = shapeDF['HDangle2'].to_list()\n",
    "HDangle3 = shapeDF['HDangle3'].to_list()\n",
    "HDradius, HDangle = list(), list()\n",
    "for t in range(nHDs):\n",
    "    HDradius.append( [HDradius0[t],HDradius1[t],HDradius2[t],HDradius3[t] ] )\n",
    "    HDangle.append(  [HDangle0[t], HDangle1[t], HDangle2[t], HDangle3[t]  ] )\n",
    "print(\"I have read back in the original HD shapes\")\n",
    "popHDlist = list()\n",
    "HDpoly = [dummyPoly for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001:\n",
    "        popHDlist.append(t)\n",
    "        HDpoly[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t])\n",
    "if \"pigs\" == \"can fly\": #countyNo in shapeDF.columns.values:\n",
    "    HDcountyNo = shapeDF['countyNo'].to_list()\n",
    "else:\n",
    "    print(\"County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\")\n",
    "    HDcountyNo = [-999]*nHDs\n",
    "    for t in popHDlist:\n",
    "        for c, geom in enumerate(countyGeom):\n",
    "            if geom.contains(hdCP[t]):\n",
    "                HDcountyNo[t] = c\n",
    "                break\n",
    "    unassignedList = list()\n",
    "    for t in popHDlist:\n",
    "        if HDcountyNo[t] == -999:\n",
    "            unassignedList.append(t)\n",
    "    if len(unassignedList) > 0:\n",
    "        print(\"I found\",len(unassignedList),\"populd HDs whose centers fall outside vtd-based county lines.  Assign to closest county\")\n",
    "        for t in unassignedList:\n",
    "            minDist = maxD\n",
    "            for c in range(nCounties):\n",
    "                dist = countyGeom[c].distance(hdCP[t])\n",
    "                if dist < minDist:\n",
    "                    minDist = dist\n",
    "                    HDcountyNo[t] = c\n",
    "        print(\"FYI, here are those manually assigned HDcenters to their counties\")\n",
    "        for t in unassignedList:\n",
    "            print(t,HDweight[t],\" is the HD row and its weight in the ensemble\")\n",
    "            plotPoly(hdCP[t].buffer(0.1))\n",
    "            plotCenter(int(HDvPop[t]),hdCP[t],6)\n",
    "            plotPoly(countyGeom[HDcountyNo[t]])\n",
    "            plotPoly(MAP,0.2)\n",
    "            plt.show()\n",
    "print(\"Ready to capture unit centroids based on these HD poly shapes; see next block\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c47fa1ff-2bed-4641-96e9-8dbdb7cb6da9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on cluster no 0 containing counties [41, 52, 54]\n",
      "halfway there! last use was 0.87722\n",
      "our final fractional capture area to normalize this cluster's usage is 0.01377 from 423 intersecting HDs\n",
      "working on cluster no 1 containing counties [58, 48, 38, 61, 63, 32, 9, 31, 50]\n",
      "halfway there! last use was 0.98116\n",
      "our final fractional capture area to normalize this cluster's usage is 0.87923 from 387 intersecting HDs\n",
      "working on cluster no 2 containing counties [42, 17, 57, 56, 34, 3]\n",
      "halfway there! last use was 0.9525\n",
      "WARNING, only 0.95714  of a district's worth of ensemble intersected the cluster geometry\n",
      "our final fractional capture area to normalize this cluster's usage is 0.0 from 416 intersecting HDs\n",
      "working on cluster no 3 containing counties [4, 36, 45, 5]\n",
      "halfway there! last use was 0.84851\n",
      "our final fractional capture area to normalize this cluster's usage is 0.48425 from 480 intersecting HDs\n"
     ]
    },
    {
     "data": {
      "image/png": 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2AvKPQ69bYPIK8Dp3BqrwsNQfQrAImiXa1q1JWL6cgqL+5Oz3QyrSkbjx/7hteHu0Wi2//PILv//+O00k67/ByDFaWHcwm/WHdAT6eDC8QyRD2oXj4+k+Sz41seV4HgMShXelqaHIMtlvvkn2Sy+j8vEh/tN5BI4de+aAfV/DorFQkg8jXoAxc0B9fplpwsNSf4hPVNBs8YiIIGHxYkoCRpG5LRAsRqJ+v4e7h0Tj7+/PX3/9xTfffIPdbm9oUxsVZpuDTUdzWHcwm4zCEoYlOZd8WgR5N7RptUJRFEqsDrw8RIXZpoRssZDx6KPkz1+AJiqKhKVL8O3f37lTUWDT27BqBiDBhIVwyYPOasPniaIowrtSTwjBImjWqP38iPv4Y+RON3D672AUm53ANQ9yT28N4eHh7N27l2XLllXqDC44G0VR2JeuZ93BbLadzKdPyxCGd4ikW1xQoz15bz9VQJ+WIQ1thsCFOAoLSZ0xA8PPv6BNSqLliuV4lTUodNjg+/udqcs+oXDzD9Dp2lrPIcuy8K7UE+JTFTR7JE9PYl5/Hc/R/0fqHyHINgnvDc9xRxsd8XFxpKSksHDhQoxGY0Ob6nZk6c38nuxc8okI0DK8QySXtg1vEl6JgiIrwfXUQFFw8bGmp3PyxsmUbN+B76BBJHy5GI/I0lR1s97ZE2jXYghtA7f9DvH96jSP8LDUH0KwCASU1mp55GEC7nqJU+vCsJWo8dg8h1tCdtAxqR2ZmZnMnz+f3Nzchja1wTHbHGw84lzyyTVZGN7BueQTGeDV0Ka5jOQMAx2iRYuPpkLJvv3OtOUTJwgcP564jz9C7VdaiLAwDRZcAcc3QPxAmLEWQlrXeS7hYak/xKcqEFQgZMoUwl6ay6k/orEYNKj2LGGC/B39e3WjsLCQBQsWkJ6e3tBmXnQURWFXagHrDmaz41QB/Vo7l3w6twhskneTpwtLiAtxzzRrQe0wbtjAqWnTcOTmEnb/fUS/8jKSR2kAbcYu+Gw46JKhy0SY9i34XNgyoPCw1B9CsAgE/yFg5Ehi5i4i7d9WlOR6IB35lVHZH3LFkH4UFxezcOFCDh8+3NBmXhTSC4pZdzCbDYd1xIX4MLxDJIPahKHVNP4ln+pIzSsmLqRxBQgLqqZg+XLS770PxWYjevZswu+994yYOPwLfH4lmLJh8OMwfh5oLrz9gvCw1B/iUxUIqsCnVy/ivljB6UOdMGVokdK30W//c0wcNRBZllm+fDk7duxoaDPrhSKLnT8O61h3MBuj2c7wDpEMS4okrJn00jmcbSQpSiwHNWYUWUb39ttkzXoBlbc38fM+Iejaa84csPUTWD4ZHFYYNxeGPV2rTKCakGVZeFjqicZRDEEgaAC0iYkkLPmKtDtvx27ZShBH6PD3/dxy1ft8+dt2fvjhB4xGI0OGDGn0JyhZVtiVVkBhsQ1vTzWD2oThoW5+9zN5JgvBPhe/E7TAdchWK5kzn8Lw009oIiOJm/cJXu3bl+50wG9Pw9aPQBsIkxZD6yEunV9RFGS7gs3qwMOz6XoiG4Lmd0YSCGqBR2QECV8uQa+6gtxkPyRTFnG/zeCOK7ri6+vLH3/8wQ8//IDD4WhoU+vEqbwi1h3M5o8jOlqH+TG8QyQDE5unWAHYcaqAXgnBDW2GoI449HrSZtyG4aef0LZr50xbLhMr1iJYMdUpVgLjYcYal4sVh0PGbnWgUqtRZFF00tU0z7OSQFAL1H5+xH8yD0vCFLJ2BIDFQOhPt3L30HhCQ0PZuXMnK1aswGq1NrSp54XRbGPDIeeSj80hly/5NPcU3mKrHW9PdaP3ljVXbKdPc3LyFIq3bcN34AASlnyJR1SUc6cx2xmvcvhniOnpbGAYkeTS+a0ldlJ26pDUoFJJbt1yorEiBItAcB44a7W8hmrIA5z+JxhsFnx/vIs7emmJjY3lyJEjfPHFFxQVFTW0qVXikBX+PZHPuoPZJGcYuLRtGMM7RNImwr+hTXMbNqfkMUA0OWyUlBw4wIkbbsCakkLgNdcQ9/HHqP1Lv9vZyc5MoMzdkDQGbvkJ/CJcOr+pwEz64QLa9o50xrAgIQnB4nKEYBEIzhNJpSLi0UfxmfYyqX+GItsUtGse45bWObRr25bTp08zf/588vPzG9rUclJyTKw7mM3GIzm0j/JneIdI+rUORdNMl3yqw+5w9n8Rn0vjw7RxI6dumoYjJ5ewe+4hevarSJ6l3sKUDbBgFOjTYMB9MHEReLo2XT0/o4jC7GJadw9HkqTStGaVECz1gPjrFAhqSchNUwl+6mNSN0VhN6vQbHyNGwK207NHd/Lz85k/fz4ZGRkNZp++2Mb6Q9msO5iNSpIY3iGSoUkRBHqLYNLq2HI8XzQ5bIQUrFxJ2t33oFgsRL/yMuH/d/+ZJb2di2HJ9WA1wZVvwahXQOXaINis43rsNgexSWdqt5RlCYmVRdcjsoTcjKNHXyUk5JJavKIssMvVfx1VjdvQc9V2/gsZt6a5FOitRfvGYxz9+F1aR2eg3bGAUYkHCbz0CnbtT+abb15m8OBLiYmJqcVcFZFAUiEhlf4uIaGq8HvlbQ5ZITnThMUu46f1pFd0ACqVCkkqxGSi0liSVHafoio9uUuVf69qrvLXlf1e/bbK40puHxOiKAolNkej6SAtcP6b5cz5H3mffILKx4cW//sffpeWnjdlGTa87Gxi6OELEz6HdqNcbkPqgTwCwrwJiqzssSkrHOfu3/vGiPgLdTNCQi4hNHRwQ5shOB9ChxAaNoTT90wnOukg3mxmsE0iqP9Mvv11A998c5SxYzvQvXv3Wg+tKAoglz+CgqJQ4Xfn4zGdkdMFRahU0D2+Bb6e6tL9ivMR2dmBtsK2iuMqSoW5UEBxLo2c+f3MXE675P+MW9U2pfT1ZbaXIXG2OKutmKtujLpug6M6I20CvMnLO1Tvc9XvuOdL1ePaHUWEBA/Cw8O9a9AoVisZTz+D4Ycf0EREEPfJx3h16ODcaTPDd/fA/lXgFwVTVkJ0N9fOLyuk7Mohpm0QPgFnB6rLsoxiyGfR4/czeOqttOzaw6XzN2eEYBEILgBtmzbELf6a9LtmEG7dih//0LX4MfzGvcOyHzfw7bffYjQaueSSS2p1x+U8Vl2lWzm/yMqu1AIA2kUGMbxTjIveTfNkR1YW/WOjGtqMBqW4+BTFxcfdXqw4DAbS7/8/irduRdu2LXHzPsEjOtq5sygPVkyB1M0Q0ckpVgJjXTq/3erg+O4cWnUPr7LGiqIoaPR5yJknyVEU0pP3C8HiQkQMi0BwgXhERhK/aBl55ivRn/JGyj1E63W3c9s1Q/Dx8WHdunX8/PPPyLJ87sGqwWqX+edYLusOZnMyr4ih7Z0NB0W/mwvjUJaB9lHNO1PKaDyAxaojLGxoQ5tSI7aMDE5NmULx1q349O/vTFsuEyt5KTB/hFOsJA6HW391uVgpMVo5uS+PNr0jqxUrW1YvxzvjRLn3UeBahGARCFyA2t+f+HmfYgqdSt5hXyTjaSJ/mMIdV/YkKCiIbdu28dVXX2Gz2c57TEVRSM4wsO5gNpuP59E9PojhHSLpGR8sajy4iNS8YhJCfRvajAajoGArIBEc1KehTakR88GDnJx0A5ajxwgcN5b4eZ+gDij1Bp3aDJ+NgPzj0OsWmLwCvFzrKdLnFKNLNdKmV0SVf3uyw8HaTz/gn5VLkNUa1LFtAJdV+xeUIgSLQOAiJE9PYt54A3uPB8neHYBk0RP4zRTuHNaa6OhoDh48yOLFiykpKalxHJ3RzLqD2aw/pCPQx4PhHSIZ0i5cBIW6mLT8YloEN88mh4qikJO7Di+vaPz9Oza0OTVi2vQXp6ZMxZ6TQ+jddxH92mtn0pb3fQ2LxkJJPox4AcbMAbVrs+FyUo0UG2wkdKo6i8xqLuHbN19i37rfCIqKprhlEmr/0mrJQrG4FCFYBAIXIqlURD7+OB7jXyFjazDYzHitvplbe3mTmJhIamoqCxYsoLCwsNLrzDYHm47msO5gNpmFZoYlOZd8WgQ1zwvqxeBgpoFOMYENbcZFR1Ec6HQ/ERjQA2/v+IY2p0YKv/6atLvuQrZYiHrxBSIeeMAZ36UoziygVTMACSYshEsedLlAOH24AJVaIjqx6u9JUWEBK2Y9yYld24lul8T4Z15B8fQSQqWeELdsAkE9EDJtGoaISNLfvo8W/XLw+PF+pgyfxXe+Xdmzdy/z589nypQp5Ni90RnNeGpU9GkZgpeHaJZ2MSgoshLk0/xaETgcxeTkrCU8/ArUavftvq0oCrnvv0/u3I+QfHyInfMufoNLsycdNvjxIdi1GHxC4YZlEN/P5fOf3JtLWJw//iFeVR6Tl57G6teex5Cjo23fgYy+/5HyAoSqcsEihIsrER4WgaCeCLhiFKGvLiVtazx2iwrVullc472VHn36YTQa+XT+Amz6LIZ3iOTStuFCrFxEtp8qoE/L5tXk0GLJITfvTyIjr3ZvsWK1kvnkTHLnfoQ6PIyExYvOiBWzHpZMcIqV0DZw2+8uFysOh8yx7Tpi2gVXK1bSD+5n+XOPYcjR0fPKcYx56Ak8PLVnBdYLR4trEYJFIKhHfPr0IWruKtJ2tcdapEba+jFDcpdw5agROGxWflq9kv379ze0mc0Ks82BVqNqVoW9iotPYDIlExkxukLhQPfDYTSSeued6L/7Ds/ERFotX453p07OnYVpsOAKOL4B4gfCjLUQ0tql81tK7BzfmUPrHuFovategDi8eRNfv/wM5uIiLpt2O0Nvvh1VaQVdpTQ7SEJ4WOoD9/3mCgSNHEVR2J1WyF/2ADJnLSAjpQ/mAg1BJ36gz8HXuHH8GAC+/vprNm/e3MDWNh82p+Q1qzL8BsM+rLZ8QkOHNLQpNWLLzOTU5CkUb96CT58+tFy6BI8WLZw7M3Y5GxjqkqHLRJj2LfiE1DhebTHmm8k4UkCb3hGoNWdfGhVFYdsPq/lxzusgSVz90JP0umpcpWPKPCzNSAtfVEQMixuhiNz9JkF6QTGHs4xIEnSNDaJ7XBAQieOLrzn9f3cSaluLL5toV/x/3DLhA5Z8u4bffvsNg8HAyJEjUanEfUR94ZAVHLKCRzNpcphfsBlPjxAC/Lo0tCk1Yj50iLQ778KenU3AmDFEv/oKqrJMoEM/O4NrbcUw+HEY+pTLFUHeaRMlJhutuoVXuV+WHWxY+Cm7f/sRLz9/rnnsWVoknZ1dVX4OL/ViNScv3sWgefzVNhqU8i+6oHFRZLHzx2Ed6w5mY7LYGd4hkmFJkYT5nYkVUPv7E/vJQgq9JmNI80LKPUDsjzdx+3XDCQgIYPPmzaxevRq73d6A76Rps+V4Hv2bgXdFURRyctbi7RWPn1/7hjanRkx//+1MW87OJvSOO4h54/UzYmXLx7B8MjisMG4uDHva5WIlM0WPwy4T277qmCabxcwP78xm928/EhgRyY0vvVmlWIEKHpayDUKvuBThYXEjFEWusPYpcHdkWWFXWgGFxTZ8PDUMahN2zjt3lacnMW+9i+7NGBx75xDcNp2QryZwx4QlLP59L/v376eoqIhJkybh5VV1wJ+gbiiKQpHFjp+2aZ/2ZNmOTvczoaFD8PBw77TtwtXfkPnccyDLRM2aRfANk5w7ZAf89jRs/Qi0gTBpMbR2/ZLWqQN5BIZ7ExRRdcXoYoOeb19/kcxjh4ls3ZZrn3gO36Dqg7XPxLBQ+ijO567kgm7nZ8+ejSRJPPjgg+XbbrnllvJOlWU//fv3P+dYq1atomPHjmi1Wjp27Mg333xzIaY1UmSEJHd/TuUVse5gNn8c0dE6zI/hHSIZkBh63ssMkkpF5BNPoIycjW6fP5K1AN9l45kxtDUtW7bkxIkTfP755xgMhnp+J82LXWmFdI8Pamgz6hW73YRO9xMREaPcWqwoikLOBx+S+dRTSB4exM798IxYsRbBiqlOsRIYDzPWuFysyLLCsR06wuP8qxUrBZmnWfbMo2QeO0zrnn2Y9PzsGsWKc9yyGBZxHq8P6ixYtm3bxrx58+jatetZ+6644goyMzPLf37++ecax9q8eTOTJk3ipptuYs+ePdx0001MnDiRrVu31tW8Rori1hH8zRmj2caGwzrWH8rG5pDLl3yCfeteyyPkllvwuu1TMneEgN2Mx/IbuamHD507dyY7O5v58+eTk5PjwnfRvMkzWYnwb7peK4slm/z8v4iMHItK5cZpyzYbmU8/Q+4HH6AOCyNh0SL8L7vMudOYDZ9fCYd/hpiecPs6iEhy6fw2q4Nj27Np2SW0ym7LABlHDrHs2ccozM6k28grGffoM3ich8fzrCwhIVxcSp2ujiaTiSlTpvDpp58SHHy24tRqtURFRZX/hITUHM09Z84cRo4cycyZM0lKSmLmzJkMHz6cOXPm1MW8Rovzyy4Ei7vgkBX+PZHPuoPZJGcYuLRNGMOSImkT4bpmeQGjRxPw7Aoydsag2B2ov7md8THZDBgwAL1ez/z580lNTXXZfM2Vo9lG2kT4NbQZ9UZRUQom0xEiIq5w67t7h8lE2p13oV+9Gs/WrWm5fBneXTo7d2YnOzOBMndD0hi45Sfwi3Dp/MUGK6n782jbOxJNFQ0MAY7++w9fvfgUJUYDl06+heEz7kalPr8aSeV1WMr1ivv+WzRG6nR1vPfee7nqqqsYMWJElfv/+OMPIiIiaNeuHbfffjs6na7G8TZv3szll19eaduoUaP4559/qn2NxWLBYDBU+mn8yMLD4gak5JhYdzCbjUdzaB/lz/AOkfRrHYqmnjJLfPv2JfSd7zi9tx0Oq4RqzVNcziYuHzkSs9nMokWLOHjwYL3M3Vw4kVtEq7Cm2eRQb9iD3W4gNPTShjalRmzZ2ZyaehNF//yDd+9etFy6BM/Y0o7KKRtgwSjQp8GA+2DiIvB0bSfywuxictKMJPaMQKqmeejOX37g+3dmI8syV97/KH3HXV8r0XEm6FYIlfqg1mfg5cuXs3PnTmbPnl3l/tGjR7NkyRLWr1/P22+/zbZt2xg2bBgWi6XaMbOysoiMjKy0LTIykqysrGpfM3v2bAIDA8t/4uLiavtW3A5Fkc99kKBe0Bfb2HDImeWjkiSGd4hkaPsIAr1d20itOrzatSNq3g9kHO2FrViFtPl9+md8znXXjkOWZVauXMm2bdsuii1NjYzCEqIDm2ZPpvz8v1GrfQgM7NHQptSI+fARZ7flQ4cIuHI08fPnow4Kcu7cuRiWXA9WE1z5Fox6BVSurfqsO2XAXFR9A0NFlvlj8Xw2LPwErbcP1z/9Ih0uuazW85xJa74AYwXVUqtw+bS0NB544AHWrFlTbQbDpEmTyn/v3LkzvXv3JiEhgZ9++onx48dXO/Z/VayiKDUq25kzZ/Lwww+XPzcYDE1AtIgYlouJ3SGz7WQBxVY7gd4eDGkXXmXr+IuFR1QUMfO/IfP/ZhAevB7tga/oZNThN2k2y1d/z08//YTBYGDYsGHC1VwL9p/Wc3mnqIY2w6U405bXEBDQFS+v6IY2p0aKNm8m/f7/QzaZCL1tBuEPP4ykUoEsw4aXnU0MPXxhwufQbpTL508/lI93gCcRCVUvCdqtVn6Z+y5HNm/CPzSc8TNnERaXUKe5zvKwiL9Tl1IrwbJjxw50Oh29evUq3+ZwONi4cSMffPABFosF9X/W+qKjo0lISODo0aPVjhsVFXWWN0Wn053ldamIVqtFq3XfwLK6IGJYLg5Hso2k5RejVkn0bhniVmmu6oAAYuYtIfPJBwnOXYkPf5JQfAe33vApi1f9zKZNmzAYDIwdO/asvzXB2eiLbQRcJC/ZxUKWreh0vxIWNhSNxnXxVPVB4bffkvnMsyDLRD77DCFTpjh32Mzw3T2wfxX4RcGUlRDdzaVzK4rCiT25RCT44xdc9Q12icnId2++xOlDyYS3bM34J57HL6TudXrKg25LhYq4sXAttTpTDx8+nH379lXaNn36dJKSknjiiSeqPIHm5eWRlpZGdHT1dwEDBgxg7dq1PPTQQ+Xb1qxZw8CBA2tjXhNAxLDUF/lFVnanFQDQNsIZl+KuOGu1fIDu9Rgcx9/Dn/2Er5rI7ROXs/j7P9izZw9FRUVMmDChyYl2V/PvyXyGJ7k2cLMhsduN5OZuICJiNCqV+woxRVHI+/hjcv73HpKXFy3eeRv/YcOcO4vyYMUUSN0MEZ2cYiUw1qXzO+wyKbt0tOwchmc1PYH0uixWzZ5FQUY6Lbv15OqHnsTT+8LiZkRp/vqlVoLF39+fzp07V9rm6+tLaGgonTt3xmQyMWvWLK677jqio6M5efIkTz31FGFhYVx77bXlr5k2bRotWrQoj4N54IEHGDx4MK+//jrjxo3ju+++4/fff+evv/5ywVtsPDhjWMQ33VVY7TLbT+ZjtjsI8vHksnYRDbrkUxsklYrImc+Q93k0heufISgxDf/FY5gx5WuWrtvDsWPH+OKLL5g8eTJ+fk03++VCMNsceGpUjebf/FyYzRkYjfuJjLzare/cFZuNrBdfpPCrr1GHhhL38Ud4dyltDZCX4oxXyT8OicNhwkLwCnDp/JZiG6kH8knsGYG6mkD5rJSjfPP6CxTrC+k8dCQjbrsXtebCPa1n2qu4779PY8alvnC1Ws2+fftYtGgRhYWFREdHM3ToUFasWIG//xnXZWpqaqV+KQMHDmT58uU888wzPPvssyQmJrJixQr69XNt23D3RxbS/AJRFIXkTANZejMeahW9Wwbj4+k+Sz61JXT6DAwRUeQuupuwDgVoF43h5snL+Xq7L4cOHWL+/PlMnTqV0NCmX26+tmw+nsegxLCGNsMlmExHsFpzCA+//NwHNyAOUxGnH3qIok2b8GzZkrhP5+FZFlt4arOzzH5JPvS6xRlgq3atl8iYbyY33USb3hHVirrjO7fxw5zXsFssDJwwhf7X3eAyAfhfD4s7C8vGiKQ0kY57BoOBwMBA9Ho9AQGuVewXC4s1F6tFh79/1X0qBNWjM5rZl64HoEN0ADFBTSsrpGjrv5jenEJEJx1IauTrF/DrKQ+2bduGj48PkydPJjbWtW71xowsK6w/pGNER/dd+jtf9PqdSJKGgICzi3S6E7ZsHWl33YXl4EG8e/Yk9sMP0JTV6dr3NXx7t7Mn0IgXYNAD9dLA0Gyy0aKankAAe3//ld8/m4ukkhh5x/10vqzq0hx1JSUlhcWLF9PKx5/cHRsYPPVW+lxdfbKJwMn5Xr9FwIQ7ocii+WEtMNsc/HU0l/WHssksNDMsKYLhHSKbnFgB8O3Xl8BXfiLrQEsUhwPVVzczOiSd4cOHU1xczBdffMGRI0ca2ky3YcuJPPq2rrlgZWMgL28TGk2Q24sVy9GjnLzxBiwHD+J/xRXEf77AKVYUxZkFtGoGIDmXgC550PUNDI8VIjuUasWKoij8tXwRaz/9AA8vLdc+8bzLxQpU0fxQ4FLE1dGNUBDND8+FoijsS9ez/lA2207m07tlMMOSIukWF9Tk3a9e7dsR9v6vZB3rimyTUP32OIOK13HNuHE4HA6WLVvGzp07G9rMBkdRFIxmOwFe7huUei4URUan+xU/v/b4+rZuaHNqpGjLVk5OnoI9I5OQ6dNp8c7bqLRacNjg+/th3YvgEwo3/wCdrj33gLXk5L5cfAI9CY+vOmPKYbfxywdvs/WblfgFhzBp1uu07NbT5XZAxTospVlC9TJL86XxLu43RYSHpVqy9GYOZOiRJOgUE0iXWPdt7FafeERHE/nJT2Q/OJWI8E1oNr9Ll44Z+E56iJVfr+b777/HaDQyePDgJi/gqmNPup7ucUENbUadkWVLadryCDQa967Oq//hRzKeegrsdiKffpqQm6Y6d5j1sPJmOL4BQtvAlK8gxLXCS5YVUnbqiG0fjLd/1T2BzEUmvn/7VdIO7CU0Np7xM18gICzcpXZUtuk/HpZm+jdYXwjB4kYoiiI8LBUosTrYdjIfuywT4e/FsKTqA+maE+qAAKI++orsmfcSYluNNnkFrY06pt/0DktWrGLDhg0YDAauvPLKZlmrRWcwN1rBYrMVkpe3kYiIq1Cp3Pf0rCgKefM+Jefdd5G0Wlq8/x7+Za1aCtNg6UTQJUP8QLhhCfi4dnnOZnFwYm8OrbuHo/Go+jtuyM1h9eznyUtPJa5TV8Y+8hRevvWbUXeWh0Wcr1yK+/5FNEtE4ThFUdidVkh+kRUvDzX9Woeg1TS/i+65UGm1RL01j5zXovHP/AhvNhD57TRum7KYxV//wI4dOzCZTFx33XV4eta9o3Rj45jOROvwxpnmXVKSjqnosPunLdvtZL34EoUrV6IODibuo7l4d+/u3JmxC5ZOAlM2dJkI4z4AjWtrBRXpLWSl6GnbK7LankC6k8f55rVZmAry6XDJZYy6+wHUmvpfIhQxLPVL8746uh2yW5+o6pP0gmLWH8pmw2EdcSE+DO8QyaA2YUKs1ICkUhHx1EsUd38FU6YWdf4+Ar68mtsmjqZFixYcPnyYRYsWUVxc3NCmXjRO5BY1yq7MJtNhzOZ0wsOGu/U5QC4qIu3eeylcuRLPhARnt+UysXLoZ/j8SqdYGfw4jJ/ncrFSmF1M3mlTjQ0MT+7dxYpZT2AqyKfftRMZfd8jF0WsQMVuzWW2ue+/ZWNEeFjcCGfhuOajIYssdradzEdWFGKCvBmW1PhTUBuC0Bl3oo+IQr/6bgIT0tB+NpKbb/2Rrzbs4ejRo+W1WoKDq0/3bApkG8xE+De+yr+FhdtRqb0IDu7f0KbUiD0nh7Q778KcnIx39+7EfjT3TNrylo/h1yedTQvHzYUeU1w+f/ZJA4qsEN+x+ppD+//4nbXz3keRFUbefh9dR1zhcjtqorw0P2VLQhd1+iaPECxuhYIkNW2Pgiwr7EorQF9iw9tDw6A2YXhUU41ScP4EXj2OorAI8ufeSEhiAdKnI7jhlm/40c+PXbt2MX/+fKZMmVJji4zGzp60wkbX5DA37w98vBPw8WnV0KbUiCUlhbTb78CWkYH/yJHEvPkGKi8vkB3w29Ow9SPQBsKkxdB6iMvnTzuUj2+glpDoqoOQFUVhy6rl/PPVEjRaLVc/+CSte/ZxuR3nQgTd1i/iSuFGNOXS/Kfyilh3MJs/j+TQOsyPYUmRDEgMFWLFhfgOGIDPM7+RczQGlVKCtGAMV7dRM2TIEEwmE59//jkpKSkNbWa9YDDb8PNqPPdfiiKTrfsZf//Obi9Wirdt4+SNk7FlZBBy8zRazHnXKVasRbBiqlOsBMbDjDUuFyuKonB8Vw7Bkb7VihWH3c6aT97jn6+W4BMYxKTnX2sQsQKiNH99I64WboXSpJofGsw2NhzWsf5QNjaHzPAOkQxNiiDYt/kEgV5svNq3J+jNdWQfb4+k2JFWTmWIVwpjxozBZrOxZMkS9u7d29Bmupytx/Pp36pxtCdwOMxkZ/9AWOhQtJ7u3TpA/9NPpN46A9loJHLmk0TOnImkVoMx2xmvcvhniOkJt6+DiCSXzu2wyRzdnk1sh2D8gqte6rOWFPPtGy+yf8NagmNimfzyW0QltnWpHbXh7OaHQri4ksZzS9IMaAoeFoessONUAUazDT+thkvbhKERXpSLikdMDGHvryX70QlERPyL6rdH6NHvYfwmTuTrVatYvXo1BoOBQYMGuXWA5/lisTvQqKVG0eTQas2joGAzkZFj3Hr5V1EU8ufPR/fW28605TlzCBhV2scoO9mZtqxPg6QxMP5T8LywLsf/xVxkI+1gPm16RqCq5vxhys9j9esvkHPyOC2SOjLu0Wfw9m/YtiwihqV+EYLFrWi8HpaUHBOn8oqQJIme8cEEejfeKqNNAXVgIBEf/EDOzFsJdfyMZus7tC3M4OabZrJ0+Qp+//13jEYjo0aNqtSItDGyOSWPAa3d37tSUpJKUVEKkZFjGtqUGlHsdrJeeYXCZctRBwURO3cuPj17OHembICV08BigAH3wcgXnYG2LsSQW0J+RhFtelVfdyk37RSrX5uFMTeHdv0vYfS9D6Nxg/T98iwhQb0gBIsb0dg8LPpiGztTC5AVhdbhfiLLx81QabVEvLmI3NlPEFi4AM/Dy4k2ZjHjlrl8uewrtm7ditFo5Nprr8XDo3EKTFlWsDkUvKopHuYuGI3J2B1FhIUNbWhTakQuLub0I49i2rABj/h44ud9gmfLls6dOxfDjw86K3Jf+Rb0vd3l8+emm7CW2GjZtfqlsrQDe/nurVewFBfRa8y1DJkyHclNRHe5h6U8q7nxnM8bA0KwuBWK25fmtztktp0soMTm7NUypF14o3DFN1cktZqwp9+k4NNYfA68hBd/ELR0IjNuWsmSr38gOTmZoqIibrjhBry9G1/TyH9P5tO3lXs3OSwo+BeNxo/goIYJBD1f7Lm5pN11N+b9+/Hq1pW4uXPRhIaCLMOGl51NDD18YcLn0G6Uy+fPOFqIh5eamLbVp98f/PtPfpv7Lg6Hg6G33EnP0Ve73I4L4UyWkFTpUeAahGBxI9y5+eGRbCPpBcWoJIneLUPw04qvTmNBkiRC7ngQ/bcxONbcjy/78f50FLfc/jMrf/6D48ePs2DBAqZOnUpgYOPq0WQosbnt8qOiKOTlbcDXty3e3nENbU6NWI4fd6Ytnz6N3/DhtHjrTVTe3mAzw3f3wP5V4BcFU1ZCdDeXzq0oCqf25xEc5UtgeNWiWVEUtn2/ik1LF6Lx8GTsw4/Ttu9Al9rhCs6U5i/dIDwsLsW9b+ebG4rsVjEs+UVW1h/KZv2hbLw91AxLiuSy9hFCrDRSAq+ZCFO/wpDhh8aShsfcwUy+oh9du3YlJyeH+fPnk52d3dBmnjf70vV0buGeAktRHOh0PxEQ0N3txUrxjh3OtOXTpwmeOpXY9/7nFCtFebD4GqdYiejkzARysViRHTLHduiIahVYrViRHQ7Wzf+ITUsX4uUfwITnXnFLsQIVY1iEUKkPxJXHjVDcoJeQ1S6z/WQ+JTYHwb6eDG0vGg42JXwHDsYcvJbCt64mKC4Xx4eDuWb69/j7+/P333/z+eefc8MNN9CyLG7BjcnUl7hl126Ho5icnLWEh49CrfZqaHNqxPDLL2Q88SSK1UrEE08QcsvNzr/3vBRYcj3kH4fE4TBhIXi5NgPHarZzcl9ujQ0MbWYzP773Bsd3/EtQZDTjZ84iOLqFS+1wJWeyhJyIU6drcZ/beYEzmK0BlLmiKBzI0LP+UDZbjufRIz6Y4R0i6RkfLMRKE8SrQ0d8X/iTvPSWqCUzLLiS4dFWRo8ejdlsZvHixRw4cKChzayR4zkmWoVVXUisIbFYc8nN+4PIyKvdWqwoikLe/AWcfuhhAFrMeZfQ6bc4/95PbYbPRjjFSq9bYPIKl4uVIr2FtIP5tO0VWa1YKSosYOWLMzm+41+i27TnxpffcmuxAhXrsIheQvWBECxuhXJRBYLOaGbdwWzWH9IR7OPJsKRIBrcLx9vTvTMuBBeOR2wsQW/9SW52NyTsSF9NobdtHxMmTADgq6+cWUTuyjGdibaR/g1tRiWKi09gNO4nMuJKt1ra/S+Kw0H2y6+ge/NN1IGBxH++gIArSnvu7PsaFo2FknwY8QKMmQNq18YIFWQVkX+6iMQe1TcwzM9IZ9mzj5KVcpTE3v2Z8Nwr+AS4nzftv/w3rVnc8LkW9/2raoZcjOaHZpuDv47msv5QNll6M8OSIhjeIZKYoMaXISK4MNRBQYTMWUte0XAUB6h/f4T2J77mpptuwsvLi19++YW1a9e6XW0JndFMmJs1OTQY9mG15hEWellDm1IjckkJ6f/3AAVLluARG0vCsmX49OoFiuLMAlo1A5CcS0CXPOjyNY3sEwasJQ7iOlaf2XX6UDLLnn0MvS6b7qOuYuwjM/HQuq+3qiL/XRISuBYRw+JGKPVUOE5RFPafNpBjMuOhVtGnZYjb160QXBxUWi2hb3xF/iv3EViyDM32d2hReJpbp7/Il0uW8vfff2MwGBg3bhwajXucLnanFjKyo/vU/Mkv2IynRwgBAV0a2pQaseflkXb3PZj37sWrSxfiPpqLJiwMHDb48SHYtRh8QuGGZRDfz+Xzpx3Mxy9YS3BU9Ut5R7b+zc/vv4XDZmPw1FvpPebaRuWlKBf3ZTY3HtMbBe5xBhI4cbGHJUtv5kCGHkmCzjGBbhmgKGh4JLWakGfnov84Ft/jb+NxbAXBhixm3LKAJctXsm/fPoqKipg4cSJeXg17p2uy2PHTatziIqYoCrm56/Dz64C3t3vHVlhOnCDtjjuxpaXhN3QoLd5+C5WPD5j1sPJmOL4BQtvAlK8gpLVL51YUheO7c4hqFYhvUPWesR0/fcsfi+ejVqu56oHHSRo42KV2XAz+W5pfKBbXIpaE3AgF+YI9sCVWBxuP5LDuYDa5JgvDkiIYlhRJREDjcKkKGgZJkgi6+2lK+r+DWe+Bh+5PfOaPZfqUiSQkJHD8+HEWLlyI0WhsUDu3Hs+jnxuU4ZdlO9m6HwkK6uP2YqV45y5O3TgZW1oawZNvJPaD951ipTANFlzhFCvxA2HGWpeLFYdN5ui2bOI6hFQrVhRZZsMXn/LHos/Q+vhw/dMvN0qxAhULxzlxB2HdlBAeFndCqVtas6Io7E4rpKDYipdGTf/WoXhqhBYV1J6A626hKCya4q+n4cMBeG8wU+//nW/W/EVycjLz589n6tSphIVd/C7DNodT0KsbuLKy3W4iN3cdERFXoFK5VyzNfzH8toaMxx5zpi0/9ight97qvIhm7IKlk8CUDV0mwrgPQOPa92I22Ug7lE+bXtU3MLRZLfzywdsc3foPAeERjH/yBUJj3btuTU2UF44T1AtCsLgVtYthSS8o5ki28463a2wQPeKrL2ktEJwvvkNGYQ75FdNHY/GLOI393f5cf+86fvP3Z+vWrcyfP5/JkycTF3dxLyz/pOQxMPHiC6WKWCzZ6PW7iYwc6/Z3z3kLF6J7/Q0kjYaYt98i8KqrnDsO/ewMrrUVw+DHYehTLg+uNeSWkJ9ZcwPDYoOe7958mYwjB4lolcj4J2fhG9S4z2FnYlio/ChwCeI23I04nyyhIoudPw7rWH8oG5PFzrCkSIYlRRLm5953eoLGhVeXHmhn/oVeF4VG0qO8fwmXtw9m5MiRlJSU8MUXX3Do0KGLZo+iKFhsjgYNFi8qSsFkOkJExCi3FiuKw0HWq6+ie+11VAEBxC+Yf0asbPkYlk8GhxXGzYVhT7tcrOSkGTEVWGjZJazaz6kwK5Plzz1GxpGDtOrei0mzXmv0YgUqelhEL6H6QAgWt6LqOiyyrLDjVD7rD2WzN13PoDZhDEuKJCnKtcWcBIKKeMQl4PfKFgrz2qJWm5E+v5L+vvmMHz8eWZZZsWIF27dvvyi2/HuiYZsc6g17sNsNhIZe2mA2nA+y2czpBx+kYNFiPFq0oOXSJfj06QOyA355En59ArQBMHU19Jji8vkzjhYgSRDTNqjaYzKPHWbps49SkJlBl2GXc83jz+Hp1TTKKvw3hkXgWsSSkBtzKq+IlBwTEhI94oMI8vFsaJMEzQx1cDABb/5FwTNjCfLdirT6JjoMewPfKVNYsWIFP/74IwaDgaFDh9ar10FfYmuw739+/t94aiPw823bIPOfL/b8fNLvvoeSPXvw6tSJuI8/QhMeDtYiWHUbHP4ZAuOdmUARSS6dW1EUTu3LIyTGl4Cw6sXHse1b+el/b2C3Whg06Sb6XTvRrb1VteWsOixN6L25A8LD4mYYzDY2HNax7mA2NofMsKRIhiZFCLEiaDBUXl4Evf4LhaqxKIqCZsNjxO35gunTp+Pn58fGjRv5/vvvcTgc9TL/gQw9HWMuvjdRURR0Ob/h49Pa7cWK9dQpTt54IyV79uA3ZAgJi75wihVjNnx+pVOsxPR0NjB0sVgpb2CYGFijWNn92098/9YryA47o+99mP7jJzUpsQJnl+Zvau+voREeFjfAISvsOFWAUV+AX4CBwW3DGzwTQiCoiKRWE/TcIvQfzsQ/42M89/6PkMIMZtz6Bl8uWcKuXbswmUxMmDABT0/XiuvTBSV0irm4NYRk2YpO9ythYUPRaNyrBcB/Kdm9m7S778FRUEDQpElEPfsMkkYD2cmwdCLo0yBpDIz/FDx9XDp3WQPDxO4RqD2qvv9VZJlNy75g2/er8PT2YewjT5HQpbtL7XAXRJZQ/SIESwOSkmPiVF4RkiTRMz4Ye0AwoaENX2NCIKgKSZIIuu81jMtj8dr1HNrUr2BRBjNuW87S5Ss5evQoCxcuZMqUKfj6uqYx4am8IuJDXXuRPRd2u5Hc3A1ERIxGpXJtHx1XY1i7loxHH0OxWAh/+GFCb7/NeVefsgFWTgOLAQbcByNfBJVrA5ZNBRZ0Jw207R1ZrSfBbrPx69x3OfzPRvxCQhk/8wXC41u61A53wt3aWDQ1xJLQRUZfbGPDIWeWj0qSnEs+7SMI9HbvE6NAUIb/DfdhHfkZFqMH2sK/Uf9vBNNuvJ727duTkZHB/Pnzyc/Pd8lch7OMFzW43GzOoKBgM5GRV7u9WMlf/CWn/+8BFFkm5s03Cbvjdqdw2LkYllwPVhNc+RaMesXlYiU/s4iCrCJa9wivVqyYTSZWvfosh//ZSHh8Sya//HaTFisgloTqG+FhuQjYHTLbThZQYrMT4OXBkHbhqMSSj6AR4ztiPObQKEoWXYd34GGsr/dj4kN/8LOfHzt27Civ1dKiRd2rwOaaLIT6XbzYLVPRUawWHeHhl1+0OeuCIsvo3niT/IULUfn7E/vBB/j26wuyDBtedjYx9PCFCZ9Du1Eunz/ruB5JJRHXofqsLUOOjlWznyf/dBrxXboz9uGZaH1c43VzZ85aEhKCxaUIwVKPHMk2kl5QjFqloldCMH5a8XELmg5ePQZiDdpI0ZyR+AZnYXurL1fe+zsBAQFs2LCBhQsXMnHiRNq2rVvA6s5TBRetyaFevwtJUhMSMuiizFdXZLOZjMefwLhmDZqYaOI/+QRt27ZgM8N398D+VeAXBVNWQnQ3l8+fmpyHf4hXjQ0Ms0+k8M1rsygqLKDj4GFcfuf9qDXu7a1yFWeV5m84U5okF7QkNHv2bCRJ4sEHHwTAZrPxxBNP0KVLF3x9fYmJiWHatGlkZGTUOM7ChQuRJOmsH7PZfCHmNQj5RVbWH8pm/aFsvD3UDEuKZEi7cCFWBE0Sz1Zt0T77LyZ9LB4eBpQPL2VQtCfjxo3DbrezbNkydu/eXetxiyx2vD3VF8Wlnpe3CY0mgICArvU+14VgLyggdfqtGNesQduxAy2XL3eKlaI8WHyNU6xEdHJmArlYrCiyQspOHaEt/GoUKyd272DFrCcpKiyg/3U3cMU9DzUbsQJnF44TuJY6C5Zt27Yxb948unY980deXFzMzp07efbZZ9m5cyerV6/myJEjjB079pzjBQQEkJmZWemnoTvDni9Wu8w/x3JZfyibU3lFDG3vbDgYF3JxgwUFgoZAExaBz6vbMRR3QuNhQVp0FZ1tJ5k8eTJqtZpvv/2WjRs31iqDYsvxPAbUc5NDRVHQ6X7Fz689vr6J9TrXhWJNTeXUDTdSsmsXvoMvpeXixXhEREBeCswfAambIXE43PorBMa6dG67zcHR7dnEdwrFN7D6itr71q/hm9dfwG61MPKO+xk0cWqzi+E4E8NSuqGZvf/6pk63/SaTiSlTpvDpp5/y8ssvl28PDAxk7dq1lY59//336du3L6mpqcTHx1c7piRJREVF1cWcBkFRFJIzDWQbzHioVfROCMHbs+HKhgsEDYnK2xv/2ZswvHwdAZoNSD9MJ37QK9xyyy0sWbKE9evXYzQaGT16NCpVzfdJ9tImh5pqGua5Alm2oNP9RljYcDQa946tKNm7l7S77saRn0/QhOuJev55Z9ryqc3OMvsl+dDrFmeArdq13owSk5X0QwW06R1Zbdydoij889UStqxajofWi6sfepJWPXq71I7GgohhqV/qdEa49957ueqqqxgxYsQ5j9Xr9c50yKCgGo8zmUwkJCQQGxvLmDFj2LVrV11Mq3d0RjPrD2Wz4bCOYB9PhiVFcmnbcCFWBM0eSa3G/7lvMARNQULBc/NThP75ITNmzCA4OJht27axcuVKbDZbjeNsPp7HgNb11+TQZtOjy1lDRMSVbi9WjOvXc2razTjy8wl/8EGiXnzRKVb2fQ2LxjrFyogXYMwcl4sVfU4x2SecacvViRWH3cZvH81hy6rl+AYFM2nWa81WrEDFtGYhVOqDWntYli9fzs6dO9m2bds5jzWbzTz55JNMnjyZgIDqUxOTkpJYuHAhXbp0wWAw8L///Y9BgwaxZ8+eagP2LBYLFoul/LnBYKjtWzlvzDYH208WYHU4CPPTMrR99R1IBYLmjCRJBDw4F9PiFngfehOvIx+iFKQz49YPWbpsGYcOHWLRokXceOON+PicvWSqKAolVke93QCUlJzGVHSIyIgxbv83nL9kCdmvvApqNTFvvE7g2LGgKLDxLVj/Eqi1MGEhdLrW5XPnpBqxWR207FK9cLQUF/P9O6+Sum83IS3iuG7mCwSER7jclsbEf0vzu/c3rPFRKw9LWloaDzzwAF9++eU540tsNhs33HADsiwzd+7cGo/t378/U6dOpVu3blx66aWsXLmSdu3a8f7771f7mtmzZxMYGFj+U5+t7udtPE7vlsEMS4qka2yQ25/oBIKGxu+mp7EM+h92ixrvnO9Qf3gdN980lTZt2pCWlsaCBQsq3XCUseNUAb0S6qdrr8l0GLM5jfCw4W79N6zIMtlvvkn2Sy+j8vEh/tN5TrHisMH39zvFik8o3PxDvYiV00cKUKklYtoEVXuMMT+XFc8/Tuq+3cR27MyNL77Z7MUKVPCwiBiWeqFWgmXHjh3odDp69eqFRqNBo9Hw559/8t5776HRaMp7idhsNiZOnMiJEydYu3Ztjd6VKo1SqejTpw9Hjx6t9piZM2ei1+vLf9LS0mo1R23o0zIEi11UMBQIaoPPlTdjv2YZ1mJPvM1bkV+7hBuuvZq2bduSm5tLamrqWa/JL7IS6ld9YGddKSzcjixbCQ7u7/KxXYlssZDx6KPkz1+AJiqKhKVL8O3fH8x6WDIBdi2G0DZw2+8Q38+lcyuKwok9OfiHehHawq/a43JST7L0mUfJST1J+4GDue6pl/Dyq/745sRZHhYhWFxKrZaEhg8fzr59+yptmz59OklJSTzxxBOo1epysXL06FE2bNhQp1LziqKwe/duunTpUu0xWq0Wrdb1J7aq6NcqhHWHdBetJoRA0FTw6jcKa/BaLPOuxNsvBfPLvYkZ9BpV3YokZxjqpaptbt4f+Hi3xMenpcvHdiWOwkLS7r2Pkh070CYlEffJx3hERkJhmrMnkC4Z4gfCDUvAp/qibXWa2yFzfGcOcR1D8PKtPhbm1L7dfP/2q1hLiukz9jouvfFmpHMEUTcnznhYhFCpD2olWPz9/encuXOlbb6+voSGhtK5c2fsdjvXX389O3fu5Mcff8ThcJCVlQVASEhIeVO0adOm0aJFC2bPng3ACy+8QP/+/Wnbti0Gg4H33nuP3bt38+GHH7riPV4wKpWEl4eKYqsdH09RT0UgqA2e7bpjf2wrJW8NwdtXR48tD7NTM+Gsu8/0gmIu7+S6TEFFkdHl/EpQUF+0nvUXxOsKrOnppN1+B9YTJ/AdNIgW/5uD2s8PMnbB0klgyoYuE2HcB6Bx7Y2atcTOyf25JPaIQK2pXnwkb1zPbx+/hyLLDLv1LnqMGuNSO5oCZR6WM5+iEC6uxKVX3/T0dL7//nsAunfvXmnfhg0buOyyywBITU2tlNpYWFjIHXfcQVZWFoGBgfTo0YONGzfSt29fV5p3QQxoHcqfR3IY3kF4WQSC2qKJjEP1/C6KXh5MkNdJZrCC/JN9oU0bANLyi4kNdl3dIofDTE7Ob4SHj0Stdu96SCX79pN211048vIIHD+e6BdmIXl4wKGfYdUMsBXD4Mdh6FMuv3M3FZjRnTLW2MBQURS2frOSv1csRuOp5aqHZ9Kmt2uXo5oK5XVYVGW9hBrSmqbHBQuWP/74o/z3li1bnldxqIqvAXj33Xd59913L9SUekWjVqFSSVjsDrQakcIsENQWlV8gPi9t4+grl9OWXfj+cTdyyxhUbS7hYKbBZd4VqzWfgoJ/iIwcgyS599+qccMGTj/8CEpJCWH/dz9hd9/tFA5bPoZfn3Q2LRw3F3pMcfnc+RlFFBsstO4eXu0xssPB7/Pnsm/db3gHBHLt488R3ba9y21pKpzVrVkoFpciFh9rwcDEUP5JyWtoMwSCRovk4cnRPo+xlkvw0NiRll2Hcd/PBPm4pslhSUkqBsMeIiKucnuxUrB8Oen33odisxE9ezbh99yDpMjwy5Pw6xOgDYCpq+tFrGQd12O3OYhNqj4Wxmou4ds3X2Lfut8Ijo5h8ktvCbFyDhRFKW8tI3A9QrDUAq1GjSwr2B0iY0ggqCsK8Dd9OLw/FmQbvqun0qfwlwse12hMxmzJJixsqFtfMBRZRvf222TNegGVtzfx8z4h6NprwFoEK6bC1o8gMB5mrIHWQ1w+f+qBPLx8PYhIqD7AuaiwgBWznuTEru1Et0vihhffJCgq2uW2NDVkWXaGO5R+/SQRw+JShGCpJQMSQ9l8XHhZBIK6UuY2z8kIovjSt1FUnkjf3QN/zXEWRqsDBQX/AhAc1MdVZtYLstVKxmOPk/fpZ2giI51pywMHgjEbPr8SDv8MMT2dDQwjklw6tyIrHNuhIyzOn6DI6uN68tLTWPrMI+hOpNC270AmPPsKPgGBLrWlqXLGw1K6QegVlyIESy3x8dRgtsnIct1OrAJBc6e8VoWisF3uhHLz9+AdAr8/D789Bf+NAzjHWLm56/HyisLfv2N9mewSHHo9aTNuw/DTT2jbtaPliuV4tW8P2cnw2XDI3A1JY+CWn8DPtUXY7FZnA8OELqH4BFS//JZ+cD/Ln3sMQ46OnqPHMuahJ/DwvDjlI5oCsiwjSSqcfkREDIuLEYKlDvRtFcLWE/kNbYZA0Cgpz6RQFBQkNPF9ncsfgfGwZS6svh3s1nOOoygOdLqfCQjojrd39Y1V3QHb6dOcnDyF4m3b8B04gIQlX+IRFQUpG2DBKNCnwYD7YOIi8HRtVlOJ0crJfXm06R2JRw0tDw79s5GvX34Gc3ERl027jaG33IFK5d5xQO6GoiiohEipN0RRkToQ6O2B0Wwrd/8JBILzp6KHpXtcaRn+sLZO0fLldbD/ayjOhUlfgta/yjEcjmJyctYSHj4KtbrmNiENTcmBA8605ZxcAq+5hugXX0Dy9ISdi+HHB0GRnZ2W+97u8rkLdcXodSW06VW9x0ZRFLb/+A0bv1yA2sODqx98gnb9L3G5Lc0BWZaRVGeCbkUMi2sRHpY60jMhmJ2pBQ1thkDQ6KjoYfHRVrhnCoiG6T9DwiA4/gcsvApMurNeb7Hmkpv3J5GRV7u9WDH9+SenbpqGIyeXsHvuIXr2q85uy+tehO/vczYwvHF5vYiVnFQjJUYbCZ2rrzYuyw7Wf/4JG79cgJefP9c/87IQKxeA8yZWLAnVF0Kw1JEwPy15pnO7rQUCQWUqeljOOqF7BzlTeTtcDZl7YP7lkH+8fHdx8QmMxv1ERowuvTC4LwUrVpJ2z70oFgvRr7xM+P/dj2S3wOrbYNPb4BcFt/4C7Ua5fO70w84GhtGJ1QfL2ixmfnhnNrt/+5HAiEhufOlNYpM6udyW5oQzhkUSwbb1hHv/xbs5nVoEsv+0vqHNEAgaFRU9LFXegXp4wYQvoPcMKDjhFC0ZuzEY9mG15hEWetnFNbiWKIqC7t05ZD3/PCqtlriPPybouuugKA8WXwP7V0FEJ2cmUHQ3l899fHcOgeHeNTYwLDbo+erFpzm2bQuRrdty40tvERIT61JbmiNlMSyiWXP9IATLBdAiyJuMwpKGNkMgaFQYSpyeSUlRoLrGeSo1XPU2DH0ainJQPr8Cj7TdBAX1voiW1h7FaiXj8SfI++QTNBERJCz5Er9LL4G8FJg/AlI3Q+JwuPVXCHStQHA4ZI5t19GifTD+IdUvlRVknmbZM4+SeewwrXv2YdLzs/ENCnapLc2V8iyhcqEiFIsrEUG3F0jbSH+OZBtpF1l1cKBAIKhMkcUOlAqWmk7okoQy+DFMSh5+f87De9VDIHtDl+svjqG1xGEwkH7//1G8dSvatm2Jm/cJHtHRcGozLJ8MJfnQ6xZngK26+o7IdcFSYufUeTQwzDhyiG/feJESo4FuI0czbPpdqNQiE8hV/DcRQyRluBbhYblAWoX5cjK3qKHNEAgaBacLS9CqSzMoFKVGl7ks28nO/gGvQU8hTfrS6XVZNQO2fHSRrD1/bBkZnJoyheKtW/Hp39+ZthwdDfu+hkVjnWJlxAswZo7LxYox38zpwwW07R1Zo1g5+u8/fPXiU5QYDVxy480Mn3GPECsupjyGBVGnqz4QgsUFJIQK0SIQnA8HTuvx0zovktXGsAB2uwmd7mciIkbh4REISVfBTd+CV6CzKeDa5+tcFdfVmA8e5OSkG7AcPUbguLHEz/sEtb8/bHzLKbCQYMJCuORBlwc15J02oc8poXX38Brv5nf+8gPfvzMbWZa58v5H6XfNBHH3Xw+cESylNJGPON+cz8b0jWQVZTWoHWJJyAW0j/JnzYEsWob5NrQpAoHboi+2EejtQdY5gm4tlmz0+t1ERl5d+eSfMABu/Q0Wj4e/54ApG8a+73KPRW0wbfqL0w88gFxcTOjddxH+f/+HJNvh+/th12LwCYUblkF8P5fPnZmiR62RiG1fffyJIsv8ueRzdvz4DVofX8Y+8jTxnbu63BaBk7K05sZch0VWZFIKU8gsyizfFqwNpshWRJh3WANaJgSLy4gO9CZTX0J0oHdDmyIQuCX/nsxnRIcIDm2qPq25qOg4ZvNpIiKqSfWN6HCmwNyeZVCUCxO/AM+Lf7NQ+PXXZD4/C4CoF18geOJEMOth5c1wfAOEtoEpX0FIa5fPfepAHoHh3gRFVF8V12618suH73Bky1/4h4YzfuYswuISXG6L4AyyLJdWum08dViKbEUk5yVTYncmkKgkFYmBiVza4tJy4XUo/xBJIUloVA0rGYRgcRFdYgNZcyBLCBaBoArMNgceamcF0OrSmg2GvSiKg9DQS2seLCjOmWWzdBIcWwtfjIXJK8G3+gJprkRRFHLff5/cuR8h+fgQO+dd/AYPhsI0WDoRdMkQPxBuWAI+IS6dW5YVju/KIaZtUI09gUpMRr578yVOH0omvGVrxj/xPH4hF+fzaa6U1xdy4/pAiqJw2nSaE/oTKKWiykfjQ6fQTvh4VC1+zXYzmaZMhsYPvZimVokQLC4kxNeTPJOFUD/RLEwgqMjmlDwGtXG6kysVjit1mefn/42nZzh+fu3Ob0CfEJj2HXw9HY786uzHc9NqCKrfnkKK1Urms8+i/+571OFhxH38Md6dOkHGLqeAMmVDl4kw7gPQuPY8YLM6OLE7h9bdw9HU0BNIr8ti1exZFGSkk9C1B2Mfnomnt2v7EwnOplyIc6Zbc0P7V6wOKwfzD6K3nKkXFusXy6AWg1Cdp7DadHoTw+KG1ZeJtUIIFhfSKyGYtcnZXN4pqqFNEQjcBoes4JAVPEszWCo3P1TIyVmDv38XvLyiazewpw9MWgI/PgC7voTPRsLUVRDV2dVvAQCH0Uj6//0fxZu34JmYSPy8T/Bo0QIO/ewMrrUVw+DHYehTLl8KKDZYyTxWSNvekUiq6sfOSjnKN6+/QLG+kE6XjWDk7feh1ojT/MXgjIelQqXbi7wklFuSy5H8I9gVOxISHmoPkoKTCAoPqtN4B/MO0i64HWo3aYIpvskuRJIk/Lw0GMw2ArwaLhBQIHAnth7Po1/rM0sjZSd2VDI5hrVEthqHRlPHOkZqDYz9wFnmftNb8PmVcONSaOnafji2zEzS7rgTy9Gj+PTtS+z776EODIQtHzuzllRqGDcXekxx6bwAhdnF6HNLSOxZfQNDgOM7t/HDnNewWywMuH4yA66/UWQCXUTKhDgXKYbFITs4VniM7OLs8m2hXqH0ie6Dh+rCrz8l9hKyi7O5LO6yCx7LVQjB4mL6twpl3SEdIztGNrQpAkGDoygKRosd/woCXpZl1Gorlu4OwoNG1F2slCFJMPxZ8IuEXx53ZhHd9A20HHSB1jsxHzpE2p13Yc/OJmDMGKJffQWVRg2/PAFbPwZtIExaDK2HuGS+iuhOGZAdCgmdao4/2fv7r/z+2VwklcSoux+k82UjXG6LoGbKPSz1tBBksppIzkvG7DADzuDYNkFtaB/Svl7m25S+ieHxw+tl7LoiBIuLUakktBoVJVYH3jWsMwsEF8I7K5+j4Ojp8zq2qps8WYJKxa0U5zMFhdPmXCQkYrRnXyTPXfmkwhEqsNkV1BL88b1EekkeoyN6U5RTjLdKz7HcNuQtX4RKW33w6PlQ0YsQqR1LYvovZH7+EidiR1/QuADW7DxMW3ejePvifcVwfJLiOLLwPdqe/IYQ/RHMnuEcSpxM8fq9sH7v+Q/skCDDq+oPtPT92K0KKjWo1BL7qxlGURSycpPR5R1BpdLQMqYvWRtOkbVh/pmDLCqwqiDA5lyqkMA/MIi+945HqqHQnKB2lC91StIFpzUrikK6MZ0ThhPl2/w8/OgS3gVvTf0ndiTnJZMUkuQ2S0FlCMFSDwxMDOXPIzkM7yC8LIL64dSeQ4SP6EiMX4vybYpsP+s4Ra7iiqgo5YGBUul/VDjB6rN3EOkdRsvAllXOfW4vt4RU6h0/mmOibbgfxfZifk/+gj6tivDXyqSnRtAmfTOtLh/jXFqpI4rsqPRcnZGA17ffE9OhJSGDr63zuAD639ehW72IMFkh/N47CRg9Cqk4F7+f/w+NlIy9XWe48n+096599o0tw4whPQOfAZWziMru0gt0ZnwDPPD0rv6C4XDY2fbPN+jyjuDl7c+lI24iOKSKOKBiB5ZTxWjb+oFDQbEr7Nn4Lw6jFU1w9T2HBLWjYgxL+bLneeoVi8PCwbyDGKyG8m1x/nGVUosvFiX2EnKKc+gY1/Gizns+CMFSD2jUKlSShNUulwcaCgSuRJFgdMer6RXZy6Xjzp07l5/fXENmZiadOnVizpw5XHrpOdKMq+GYzsiARInEcGfX4ByNkc2nviRaN5pACXxtVgLDo9GEuLDxnjUVNAregUF4x9QtY0hRFHI/nEvJBx8Q4O1Niznv4H/ZZZCdDD/dAvo06DIGz/GfEuJZt+wbs6UQJcBI9JXdK2132GVSdulIGhaGp3f1p2dzkYnv336VtON7CY2NZ/zMWQSE1RzjUpH9f+2ok92C6inzsKgkFShyjcfmFOdwtOAoDsUpuD3VniSFJBGorbt4dxXuuBRUhhAs9cSAxFD+ScnlsvbnfxIRCGqDq9fKV6xYwYMPPsjcuXMZNGgQn3zyCaNHjyY5OZn4+Npf/I/nFFXKmHu6/9PsiWrFN6eOgMV5ov48eSG3X/KQy94DZR6XOrqyFZuNzOdnoV+9GnVYGHEffYR3l86QsgFWTgOLAQbcByNfrPMcTjuVs+6cLcU2Ug/kk9gzArW6+hsdQ24Oq2c/T156KnGdujL2kafw8vWruy0Cl1BxSahsrU+SJOyynWOFx9AV68qPDfcOp2903wYvxPZfDuQdoENIB7dbCirDvT6tJoSXhxq7w5nOqa4hDVEgqCuudhW/8847zJgxg9tuuw2AOXPm8Ntvv/HRRx8xe/bsWo2VqS8hKvDs5YZY/xYEa3MwmvIA+Dvjb27HhYKl9I6VOhbvynhyJoaffsKzdWvi5n2CZ2ws7FwMPz7ovGu+8i3oe7sL7KRSJzdjvpncdBNtekfU+O+qO3mcb16bhakgnw6XXMbldz2AxkNkJLoDZctAFslCpikHgL25e0nLNNEmqA1JIUkNad45KbYVk1ucS6e4Tg1tSrUIwVKPDEgMZXNKHpe0bdj+C4Kmh7PkmusEi9VqZceOHTz55JOVtl9++eX8888/tR5vX7q+2npEiqKUFo2DVkEuLlt/gR4W47p1qENDabl0CeqAAFj3Imx6Gzx8YcLn0K6algG1RLHJ5cFAeadNmE02WnWt+Txxcu8ufnjnVawlJfS9ZgKX3DBNpC03MIqikGpMJdWQislkIss7C41KS3vPMDKAbuHdiGvROHo3/XX6L0YkuHd2mRAs9YivVkOJzVHaEEucWATuS25uLg6Hg8jIyoHikZGRZGW5skOrszR/mWC5rettLhybCoKljqc2WUYdEIDa1wtW3wb7VzlrvExZCdHdXGamQ28BIPNYIRpPNS1qaGAIsP+P31k7730UWWHEbffSbeSFZ0AJao/ZbuZg/kGMVmP5toSABC5pcQkFBQVsLdlKLLGopZIGtLL2HMg9QIfQDudd/bahEIKlnunbMoStJ/Lp31r08RC4DgWlXk4u/xXWFyK2q3utoigopUGJUX4xdRq7+knLloTquAavKKg87LD4GkjdDBGdnGIlMNZlJoIze8vqqSYw0JPA8OoDdxVFYcuq5fzz1RI0Wi1XP/gkrXv2caktgurRFes4WnAUufT7qlVrSQpNIsAz4KxjK8awKI2o+WGxrZg8cx6dwtx3KagMIVjqmUAfDwwlNuFlEbgcVy4JhYWFoVarz/Km6HS6s7wu50PPhGB2phbQK+Hs5n+yLCOVFyBx8d/EhQbdSgotkvZBajEkDocJC8Hr7IvThSDLCrmpRnx9PQgI86723OCw2/n9sw/Zv2EtPoFBXPvE80QltnWpLYIz2GU7RwqOkFuSW/63FeETQf/o/ucVhFpV88P6KiLnShrDUlAZQrBcBHrEB7MrrZCe8S5M3xQ0e1wpgD09PenVqxdr167l2mvP1C9Zu3Yt48aNq/V4YX5adpwqqGKPgqIoqEsjTn9P/51RSbUfv1rqGHTrcDg4deoU+XHBdPBJxR7VHc3kFaB2bUCrzeLgxN4cohL8MfxwnNMz/0LlqyH66f6VegRZS4r54d3XOLlnJ8ExsVw3cxaBEaJHmSvRW/QczD+I1WEFQC2paRfcjo6hdas/UilLqJ70uKvZl7OPjqEd3X4pqAwhWC4C4f5adqVWdfIWCOqOq+/eHn74YW666SZ69+7NgAEDmDdvHqmpqdx11111Gq9Li0D2pevpElu5toQsy5TdrybnHWIULhQsdYhhKSkpYcWKFZw8eZLgPj0ZxB6OZhXhOHiYzp1d10ixSG8hK0VP215Oj5Vv5zAcRTZ07+0CWYFSwWLKz2P16y+Qc/I4Me07cs1jz+Dt71ovT3NDURROGk6SZkwr/7vx9/SnR0QPtGrXdNWusnCcG1NsK6bAUkCX8C4Nbcp5IwTLRaJjTAD7T+vp3KLhCwMJmgguvnubNGkSeXl5vPjii2RmZtK5c2d+/vlnEhIS6jReTJA3+07/V7BIlbKEfD19XWB5BWq5JJSfn8+SJUvIy8sjPj6eqPXboA0oksTXX3+N0WhkwIABF2xWYXYxhrzKDQzVgVokD+edrSIrSEBu2ilWvzYLY24O7fpfwuh7H0bjeWGtC5ojJfYSkvOSKbIVlVZ1lkgISKjXyrFnPCwqUNw/hmXT6U2MTBjZ0GbUCiFYLhKxwT4kZ2QJwSJwa+655x7uuecel43XLtKfw1lG2kedaXDojGFx8u2x77ijz30um6+6oFvFasWmc9bGkCTn/9Kys/n6t98oNpvplpTE6MFDOP3xq9AGElol4pXhxW+//YbBYGDkyJGoVHVzm2efNKDICvEdzw68l82l9iqQdmAv3731CpbiInpddQ1Dpt6KVMc5mxtZRVmkFKaUV4711njTIaQDfp4Xr6BeRQ9LGe4aw7I3Zy+dwzo3mqWgMoRguYi0ifDjaLaRtpEX2J1WIGgktArzZc2BrEqCpaKHJbM407UTVuFhsRw9Stqdd2HLyCjfdio+nn/79UVWq+myZy/tl6/gBM7GywDeGk9uvfVWvvzySzZv3ozRaOSaa65Bo6ndKTPtUD6+gVpCoqv2JMlmZ/+nw9s28dtHc3A4HAy95Q56jh5bq3maEzbZxpH8I+Sb88u3RfpGnndwbH1xpjS/VO5gcUcPi8lqQm/R0zW8cdSHqYgQLBeR1uF+rDmQJQSLoFmREOrLydwiWob5AkppHRbnvmCvs7OILoj/BN0WbdlK+v33IxuN+Azoj+Try25vb3b6+qJWFIYVFNIqIgIiIlBQkNP2ATlIufuJ8Ja57bbbWLJkCfv378dkMnHDDTfg5XXuhoGKonBidy4RLQPwC64+RkJRFA4W/cve9zeg8fBk7MOP07bvQFd8Ek2GQnMhB/MPYpNtAGhUGtoHt3e7NNxKHhY3jmH5O+PvRrcUVMYF+YNmz56NJEk8+OCD5dsURWHWrFnExMTg7e3NZZddxoEDB8451qpVq+jYsSNarZaOHTvyzTffXIhpbkt8qA+pecUNbYZAcNFoH+XP4ewzhbZkWUZVmkahdnUvlQpBt/offiD19tuRTSYin3mGFp9+SsqARAb5ruQZ3uNpzccMjlhJXMufiGv1M/Gt19DysmwApPwU+LAvAT5eTJ8+nZYtW3Ly5Ek+//xzDAZDDQaAwyZzdHs2sR2CaxQrssPBn6sWsFe3AS//ACY890qzFyuyInO88Dgb0zeyKX0Tm9I3kWpMpVdkLwbHDmZw7GAGxgwktA4dsuubSjEspbibg2VPzh66hHVpdEtBZdT5bLFt2zbmzZtH166V3UpvvPEG77zzDgsXLqRdu3a8/PLLjBw5ksOHD+PvX7VnYfPmzUyaNImXXnqJa6+9lm+++YaJEyfy119/0a9fv7qa6JYkRQWw5kAW8aF16/IqELgj2UXZWGUriqIgKzIyMigQ5RuFj4cPMYHeZBSW4FkWi6iUCRYXu/BLBYtx419kzPsHycuLFnPeRT1gAH988gSDcxbiiR1HcGtUKrXTI6PIIMvOR8UBvuFQlAOhbQAFLy8vpk6dyrfffsv+/fuZP38+U6dOJTw8/KzpzUU20g7m06ZnBKoaGhjazGZ+fO8Nju/4Fz/PYCa+9BrB0S1c+1k0AoptxSTnJVNid1aGlSSJVoGt6jU4tr6oqvmhO+U1m6wmjFYj3cJdV7H5YlMnwWIymZgyZQqffvopL7/8cvl2RVGYM2cOTz/9NOPHjwfgiy++IDIykqVLl3LnnXdWOd6cOXMYOXIkM2fOBGDmzJn8+eefzJkzh2XLltXFRLcmMsCLLL25yuZwAkFjY0/OHqb+PBWNpEGSJFSSCpWkwibbmNBuAk/1e4ousYH8diCLnhGlbvPS87nKxYJFcdiQAOPa31GHxBL30VyKY2PZ/8EMhhf/jIIK65Vz8Ow7vVbjajQaxo8fj7+/P5s3b2b+/PlMnjy5UhdrQ24JeRlFtOlVcwPDosICvn3jRbJSjhIZn8hAn6ubhVhRFMUZHKtPKa8c663xpmNoR3w9XJwt1gC4e1rz3xl/c3nC5Q1txgVRJ7/Qvffey1VXXcWIEZWr4504cYKsrCwuv/zMh6LVahkyZEiNDdQ2b95c6TUAo0aNqvE1FosFg8FQ6aex0C0uiL3phQ1thkDgEopsRbQMaMmuabvYedNOtk/dzr9T/uW2LrdhsJ75uwz19URf4izSVVbp9nTRaZed3OWiIgq/WgmAOiSMlsuXoQvw58TcSQwp/hm72gdl6upai5UyVCoVo0aN4vLLL8dsNrNo0SIOHjwIQG66CVOBmVZdw2oUK2nf72DJIw+SlXKUhLguDG93M5622t+4bNy4kauvvpqYmBgkSeLbb7+t03uqT2wOG/ty9pUv7fx1+i+KbEUMjBlYvrzTJ6pPkxArUCHoVqXiTGV+9/Cw7NbtpmtYV7exp67U2sOyfPlydu7cybZt287aV1bWu6oGaqdOnap2zKysrFo3XZs9ezYvvPBCbUx3K4J9PckvshLiK2osCBonZUJDVmTUVfTu8ffwJ7cklxJ7CYqi0CFGy/pdecCZJSEZBZPNhL/nhQWi23Q60u+6Gx/5OHSHsPvvJzknA88f7qE3KZi9ItHe+h1SRIcLmgdg4MCB+Pv78+2337Jy5UoG9b6Mbl17EtO25krW6YcO8O2y2VhlMx3aXkK/nuNRqVRokiJqfF1VFBUV0a1bN6ZPn851111X17fiUvLN+RzKP4SjdFlOo9LQPqR9oypMdiFUldbsDitCRqsRk81Ed7/uDW3KBVMrwZKWlsYDDzzAmjVraoyUr0sDtdq+ZubMmTz88MPlzw0GA3FxcTXO4U70Tgjm94M6RnasfZ8WgcAdmLNzDgv2L0AlqegYcnY580BtIFszt9J3Sd/ybR09oQPXUWIrDTyXJDxUF1b+3nLsGGl33IktI4OQsW2AnaQc3UdoyivEoKMkpAPet34PfrUXBtXRpUsXfH19WbZ0OX9t24DkZWdY7LBqz1lHtv7Nz++/hUO2cen10+hz/YQLutsdPXo0o0c3XMfmsuDYjKIMJJzN/kK8QugT2QcPF7czaCxU1fzQHeqw/JPxT6NfCiqjVoJlx44d6HQ6evXqVb7N4XCwceNGPvjgAw4fPgw4PSbR0dHlx5yrgVpUVFStm65ptVq0WteUVG4IJEnCV6vGaLbh79U8/8AF7sku3S70Fj0OxXEmiLb0x6E4UFBwyA62ZW3jxqQbuanjTVV2rx2bOJYhsUOAMzckOVl/8OXhXfiovUCS2DJ5C16ausdyFf37L+n33Y9sMBBy88349VNg407apMxHhUJJyxF4T14Mnq4NcpcdMo58X6ZOnsZXq5ezadMmDAYDY8eORa2u7G3a8dO3/LF4Pmq1mgHhY+k1apx7uOZrsRJXZCsiOS8Zs90MOP89EwMTG2VwbH1Rqfmhm8Sw7Nbtplt4tybzb1QrwTJ8+HD27dtXadv06dNJSkriiSeeoHXr1kRFRbF27Vp69OgBgNVq5c8//+T111+vdtwBAwawdu1aHnroofJta9asYeDApp3i179VKOsOCS+LwH0othUz7ZdptA1ui0bSoJJUqCU1kiSVP5YF1fp5+DG61Wji/Kv2bEqSRJBXUKVtRR5O4aBSAEm6oPgF/Y8/kTlzJordTuRTM9Fedx175k2nJ6BCwdzzNrzHvFHnzs3VYTXbObkvl9bdw9F4qLntttv48ssv2bNnDyaTiYkTJ6LVapFlB38ums/OX75H6+vLuIefQfqyELdYJ5Co9qKqKAoZRRmc0J8ovwj7ePjQKbQTPh4iu7E6KnlY3KBwnMFqoMhWRJRv02maWSvB4u/vf1YzMF9fX0JDQ8u3P/jgg7z66qu0bduWtm3b8uqrr+Lj48PkyZPLXzNt2jRatGjB7NmzAXjggQcYPHgwr7/+OuPGjeO7777j999/56+//rrQ9+fWqFQSWo0Ks82Bl0fDVWgUCMooshUBsHLMSjSurpHCmZO67JDrfDJXFIW8zz4j5+13kLRaWrz3P6w9evDZZ58Ro1fTVfJAGfEiXoOqbzFgzDfjH1J7z06R3kLWcWcDw7LuykFBQdx6660sW7aMlJQUFi5cyKQJE9j4+ccc/fcfAsIjGP/kC4REt+A0f7uFXqmI1WHlUP4h9BZ9+bYWfi0YGDOw0dbraAiqLM3fgIJlc8bmJrMUVIbLz0iPP/44JSUl3HPPPRQUFNCvXz/WrFlTqQZLampqpb4cAwcOZPny5TzzzDM8++yzJCYmsmLFiiZXg6UqBiSGsuloDsOShJdFUDs2pG4gpTAFlaQizj+uysDVBfsWsCVzCx4qDxyKA4fswK7Yy393KI7yGhhlXWv9PPzqRaxAxeoUSp0Ei2K3k/XyyxQuX4E6OJi4j+aSFRjIis8+w2w2k9h7CtKohWg8al4uPn24AE8vDa2615zVU5GCrCJM+RYSe5wdC+Pj48O0adNYtWoVh/fvY/7j94NRT0SrRK594nn8gkNQ7HKt3299kFuSS6Y6lb+y/0Fd4omH2oOk4CSCwoMa2rRGzZnS/Cpqtd5WD+zS7WpSS0FlXPBZ6Y8//qj0XJIkZs2axaxZs877NQDXX389119//YWa0+jwKC0uZXWTk5mgcRCrDWFf7j526nayN2cvFocFb433WceV2EuY0mEKw+OHo5bUqFVqNJIGtUpd/lxRlPIsHwXlgjN2akIpPalrpNqf0uWiIk4//AimP//EIyGe+HnzSC4o4PvFi5Flmcsvv5wBAwac10naJ8CTyFYBHN2eTZtekahUNb8m+4QzPTuuY/WtBDw8PLh8yKXofv8Bm1GPEhDMJbffj1/wf15zEa8hDtlBij6F7KLs8vogId4hRDpiGRQ+AI9wscTjKtylDoveoqfEVtKkloLKEL2E3ICBiWFsPp5HZ/erNi1wU7r4J/DkyKca2oxaU549oSiAhN0ho6mhImwZ9pwc0u66G/OBA3h360aLuR+ycfduNm3ahIeHBxMmTKBDh6pTlm0WM8kb19OmzwB8g86kHmt9PGjdPZyj27JJ7BGO2kOFgnLWMkhacj5+IVqCo2qOt8k8dphvXn8Rm1FPeMeuHJc9WLp8BRMmTKBdu3blxxV8fRSVz3mceiWJgJEJaILO9haZTCaOHTtW/vzEiRPs3r0brZ8Wk5+pPDhWJalIDEqkXXC7Sq8/av/t3PMLakWlSrcNGMOyJXNLk1sKKkMIFjfAy0ONzS4ju0lkuUBQXyiy8zuuUhQklcTm43lc2vbsEvcVsRw/Ttrtd2A7fRr/kSOIePVVvv31Vw4cOICfnx+TJ08mJiam2tef2LWd3z+by7/ffc34mS8Q2uJMkLDGQ03bPpEc35XDLvNWvFTedAvoUb7fanYQnRiIbxWioSLHtm/lp/+9gd1qYdCkm+h37UT27NnD999/z7Jly7j66qvp2bMnQde0QS62nc9HhWlzJt4dQ6oULNu3b2fo0KHlz8tKPIyZOIaVS1ZW6W2riIfGu6FXLZoc7hDDsjN7Jz0iejS5paAyhGBxE/onhrLziJHwsIa2RCCoHxRFOXPjWVpnqcTqqLHmUvH27aTdex+yXk/wTTfhd/99LFqxgvT0dCIjI5k8eTKBgYE1zmu3OqvrGnJ0LH/uca55/DngTByKSiXh2dZMR1tr8kryMHpl1aoT8O7ffmL9558gqSRG3/swHQcPA6B79+74+vqycuVKvv/+ewwGA0OGDDnvi4n5YD6K44yqsDgsHMw7iNFqRN1Gzab0TcT6xZIQkFDrC5R0YX1vBVVQsfmh0gBqUG/RY3FYiPBxXb0hd0MIFjfBT6vBbKv55C0QNG7k8nRPSVFApaJfq1C2nsinf+uz10MNP/9MxhNPOtOWZz6J48or+WzBAgoLC2nTpg0TJkyoVS2miJaJ6E6m8PVLT9P32juJ7zQKcMZ5HC44zMiEkQBkFWWx7tQ64gLizlpKqYgiy2xa9gXbvl+Fp7cPYx95ioQu3Ssd07ZtW6ZPn86SJUv4448/MBqNXHnllWfVaqmKfLWe/YUZeKQ7Y4o81Z4khSQRqK1ZoJ0fitvUCmkqVFwSaghv+ebMzYxKGHXR572YCMHiRrSP8mfbyQL6tqo+sE8gaKwoikxpzzunYJEkAn080JfYKgl1RVHIX7AA3ZtvOdOW58wht20bVnz2GRaLhb59+zJq1KjzuuiXjQfQcfBQeo8dz68fvss/Kz/Ay89Gj1Fj+Ov0X1zS4pLy46N8o4jyjSLVkMq61HUkBibSMrBlpTHtNhu/zn2Xw/9sxC8klPEzXyA8vvIxZcTExDBjxgy+/PJLduzYgclk4rrrrsPT80xbDofs4FjhMXJKcsptVmv09PLuRWBsPTVGFHrFpZR9z1SShKOqMv31yI7sHfSK6NXkb3aFYHEj/LQaDhVYhZdF0EQ5c4WUFKU8WaZnfDC70grpGR+M4nCQ/corFCxdhjooiNi5czmEwo9ffoksy1xxxRX079+/jvNLdBg0BN/AYL554yXWL/iYtNQjBLRLIDN3/5ky6tKZguqJUjAZaQfYXbKe+IB4Qr2ca7ZbvllOevJ+wuJbMv7JWfiH1ryWGxISwowZM1i6dCmHDx/m00Wf0mVEFySNcya1pKZNcBvah7Qvf02Oaj9qWSzdNBYqLgmVcxHO44XmQqwOK+E+NceCNQWEYHEzesQFsSddT/e4oIY2RSBwKc4y/87fyzwsAOH+WnamFiAXF3P6kUcxbdiAR1wcsZ98zF/Hj/PXX3/h4eHBpEmTaN++fQ0znB/xnbsy7Jan+eerdzn6+3r4HXacx+tSzhqnG2MfeQqtT83ZQ4qikGpMJdWQSpuRbcjclMmh9ENYf7Byy9RbCA6uummipJagvsodSGJFyNVUSmu+iPNuydrS5JeCyhCCxc2ICPBid1phQ5shENQDMihOkVJRsAB08LJx6MabkA4n49W1K1Hvv8f3f/5JcnIy/v7+TJ48uVJ/stpw5kJyZltgZByt7r0en4N6cCiAcqZ2RumjcmaASnU1cop12HzVDL/m1irFitlu5lD+IUw2U/m2eP94LmlxCZIkMThuMD/++CO7du1i/vz5TJkyper3ppLqV1QIxeJSKnlYyr5z9Tzn9qzt9I7s3Ww88kKwuCEdogM4kKGnU4wrgusEAvdAUf4TdFt6krUcP4H1zjuQ0tPxGz6cwBdm8eU333D69GmioqKYPHkyAQFnN1esxcSlk545qaeb04hr2YYOnauu3XLuIRV2ZO9gd94eWge25rTpNHJpgI5WraVDaIdqC/Cp1WrGjh1LQEAAf/75J59//jmTJk0iMTGx8oF2uX6veEKvuJSq0prrc0mowFyAXbET5t18UkuFYHFD4kJ8WHMgSwgWQRPjbMFSvHMn6Xffg0OvRzV+IpmTp/H14sXo9XratWvHddddd8Fd2SskUwNgl+2kGI8xuuQK8k6bkCQJSUWlR6TS5//Zp/XWoFKrkCSJ3lG9kRWZvTl76R/dH3UtmixKksTQoUPx9/fnp59+YsmSJVxzzTV07dr1zKdldqD2radO7s3jhvyicqY0v1S1eHExW7O2NpuloDKEYHFTEiP8OKYz0SbCr6FNEQhcRkXBIhcVkXrLdBSrlYjHH6dg8KX8tnwFDruVfv36MWrUqEo9x1zFpvRNDAgbiLe/B4pcWh9GUc78Lv/neYXf03UlxHUMwatUSKgkFd0jutfZlt69e+Pn58fXX3/N6tWrMRgMDBo0yHmhkxVQ16OyEEtCLuViiJQytmVta1ZLQWUIweKmJIb7seZAlhAsgiaDosiU5QZJigIOB6jVtJjzLkfDw/lxyRIA+g8ZzhVDL3XhxM4HSYIT+hPE+MXQJv7syriKopBVlEWUb1S1F4LweH9O7MklIiEAv+AL8/yUkZSUxM0338zSpUv5/fffMRqNjBo1CkWu52xBoVdcSqXCcUplr54ryTfnoyhKs1oKKkMIFjcmNtiHtPxi4kJEgzJBZWS5MV5tztRhUXl7owoMJPbDD/g7P59/fvgBT09Prr/+ek7YLiBepQrKLh4yCimFKYxIGAE4G0MezDtIka0IcN4ZR/hEkJyaTKh3aJWeE0mSaN09nLTkfOxWB0GRrvnbjIuLK6/VsnXrVoxGI4McreAcTRnrTPO6Mb8oVB3D4vp5/s36t9ktBZUhBIsb0zEmgDUHsoRgEZzFuboLuyNOD4uTwCtGk/Dii3z7228cOnSIgIAAJk+eTFRUFCVphWTpzUQFerl0/n25+4iXBrApfRMAXhovOoR0wM/zjBfTmJ9L5qa/SDPuYkfxUhICEwiLa0m3kaORKixPxXUMIfNYITaLg/B413S3DgsLY8aMGSxZsoTk5GQK1FlMtLeg5q5AdachOwo3RSo3P6yf5aF/M/+lT2SfZrcUVIYQLG5OuL8WncFMRIBrT94CwcVGQSlvflhis7Loq6/IyMggOjqaG2+8sTwTqFtcEGsOZBEVGOWymQFaBbTiktgh1QbH5qSeZPVrszDl5ZZvKyQZgNOHkxl194NoPM4EwUa3CSInzUjmsUKi2wS5xFJ/f39uueUWVq5cyfHjx1mybhU3JUw7Z7+kOiH0ikup7zoseSV5SJJEqPfZbSyaC6KMopvTPS5I1GURNA0UpTyGZffu3WRkZNC+fXumT59+VtpysK8n+UVWF83rfAj0CqpWrKTu38Py5x7HlJdLrzHXMvnlt5n00hsk3XMjYfEtOfT3n6ye/TyW4qJKrwuP88fb35O05HzX2Ap4eXkxefJk2mpakKvP47PPPiM7O9tl4wvqhzNZQqoKAc2u8YQoisK27G30ierjkvEaK0KwuDmSJBHk40mBq07eAkGDcSaGBWDAgAFMmjSpUk+dMnonBLP9pGtEQFWF4yqSvHE9q159HpvZzLBb7+Kym2YQ3bY9se064p8Yxw0vvE5cp66kHdjL8uefwFjBAwMQFOlDcLQvx3fnuGyZRaPRMNjUnv6demM0GlmwYAEnT550ydjliCUhl1JpSagUV63cbMvaRt+ovq4ZrBEjBEsjoE/LYLa56OQtEDQUiiITHh5BdHQ0Y8aMqTFtWZIk/LQajGabCy2ofPVQFIUtq1fwy4fvoFKrGfvo0/QYNabSMWpJjdpLy/iZL5A0aAi5qSdZ+uyj5KadqnScX7CWmLZBHNuuc0lAtCIrSEiMGDac0aNHY7FYWLx4MQcOHLjgsQX1wxlhXMHD4gLFkluSiyRJhHiJprhCsDQCJEnCV6vBZLE3tCkCwQWgEBAQyJ133knv3r3PeXT/1qFsOe4KoX62gJAdDtZ++gF/r1iMd0AgE597lTa9+511XOewzuzP3Y/Gw4Mr73uE3lePx5SXy/LnHicteV+lY718PWjVPYxj27Ox2xwXZnKp6JG0avr168eECRMA+Oqrr9iyZcuFjQ2AAvXUpqi5UtHDorgoikVRFLZnb2/2S0FliKDbRkL/1qFsOKRjRMfIhjZFIKgTiiJTm3sklUrCU6PCbHPg5XH+VWTPntf5WOaqt5pL+HHO65zYtZ3g6BjGP/kCQVFV9ykK1AZisBqcr1epGDL1VvxDw9nwxTxWvfIso+97hPYDztSM0XioadM7kpQdOuI7haD1qblSrfHPNMzHClHsMjgUFLuMYnc+Akga5+fVqVMnfH19Wb58Ob/++itGo5Hhw4dfYGE9sSTkSiqlNZd95y4whuXfrH/pF3W2kG6uCMHSSFCrJDRq6YJP3gJBw1H7QmgDE0PZdDSHYUkuEOoSFBUWsPq1WehOpBDdLolrHnsWn4DaZeD0HH01fiEh/Pz+W/w453VM+Xn0uuqa8v0qlUSb3hHnVWCueHcO2laBeMT6IWlUSGoVaCQktQqVjwaV15lTdMuWLbn11lv58ssv+fvvvzEYDIwbNw6Npm6ncRHC4loqNT8s4wKWhHKKc1BLaoK9qu7m3RwRS0KNiEFtwticktfQZggEdcLpYandCdxD7TxFWe0XsH5RemXOP53O0mceQXcihbZ9BzLh2VfOS6xE+kSSacqstK1dv0Fc/8zLePn68ceiz/hj0aco8hkbywrM5WeaKMwurt40m4xXhxB8e0bi0zUc706heLcPwatNEJ4xZ1e5joiIYMaMGURERLBv3z6WLl2K2Ww+30/iDBLCweJiyjwsFXsJXchYO3Q76B117qXT5oQQLI0ID7UKBQWbQyw+CxojcuW7z/NkYGIY/6TknvvAaiiLJ9jx07cYcnT0HD2WMQ89gYfn+ZXWbxfcjqOFR8/aHpvUiRtefBP/sHB2/PQdP773JnZr5Wy++I6hlBit5KQZqxzbYbDWWjgEBgYyffp0EhISOH78OAsXLsRorHr8mhGKxZVUzhKqOTPtXGzJ3EL/qP4usqzpIARLI8N58hZeluZOYyzN77zrrP0px8tDjd2h4LjQ9yxJXDbtNobecgeqWnZWro7Q2Dgmv/QW4QmtOLJ5E6tefQ6zyVTpmLKicpnHCs96vaLI2EtsOKwO7FYHdqsdu8WOvcT5YyuxYSu2YSuyYSuyYjE5f1R2NROvmUSH9h3Jyspi/vz55ObWUtQ1vq+QW1N188PaKxZdsQ5PtSdBXkGuMawJIWJYGhleHmqsdhlZVhpleXZBc6ZuHhaA/omhbDmex6A2tW/4FtM2ifD4lvS/7gba9b+kTvN7qDywOCxo1Wd7ZfxCQpk063W+f+dVUvftZvnzjzN+5gsEhIWXHxMe509hdjFpyfnEdTyTnvpTnhX7R/vrZBOAn0c4/a7sx9atW5k/fz6TJ08mLi7uPF4p1Iqrqdz8kNLfa3eOVhSFnbqdXNHyCleb1yQQgqUR0r91CFuO5zGwDidvgaChUJS6L2X6aTUUWewoSu0DdyNbt2Hamx/UeW6AbuHd2Juzt9r0Uq2PD+OffJ41H79H8qYNLHvmEcbPfIHwhFblxwRF+qDxVJOyS4dKLVFitGGXYdzdnQkI9T6raV7507JfSh+l0n3Z+/P4/aujXHHFFQQEBLB27Vq++OILrr/+epKSks79poRmcSmVPSx1+3A3Z25mQPQAF1rVtBCCpRHi7+WBqY4nb0HTYKdOw8NP/1yn11ZKtZQqPWB1yPSIC+LJ0R3o28rVhaoUqKOHBaBvqxD+PZFPv9YXv5eKj4cPJfaSGo9RazwYftsDpB60Ysr9m8VPPkpI3AQ6D+1PZKvS1gMyGPPM/LPqGDHtgmnbJ5KI9iF4etX+VOwVaERRnBfIQYMG4e/vz7fffsuKFSu46qqrzl3rRqQJuZQzpfkrBN3W4vScXZSNl9qLQG099I1qIgjB0kjp3TKE7acK6NNSVD9sjhRZJaYNa8m0AQl1HqPsnFrxsrU3vZCXfjzIxE82c+yV0WjUrgtzc3YSqvt4QT6eFJbYGlSon2tus8mG3dGPdgNiObJ5JXmnlnLwLzMH/2lf6hmRkCRo3SOcVt3CSewZjqauZQr+Y0fXrl3x9fVlxYoV/PjjjxgMBoYOHVqtvUKuuJZKlW7LOb/vqaIo7MrZJZaCzoEQLI2UEF9Ptp8U/YWaKwoSoX6eJIT6unTcVmG+JEUFMGrORnamFrrWy6LIF+RhAehR2gy0R/zFr02REJDAKcMpWga2rPYYh11G46ni6gdv4tigtvz0vzfQHfuawVOm0/vq8ZXEgywrpOzUEd/x3AXmqkKlOrsrcGJiItOnT2fJkiVs3LgRo9HImDFjUKv/I4pEWrPLqZQlVGUAbvVszhBLQeeDyBJqxHSNDWKP6OTcLFEUUF+gl2H27Nn06dMHf39/IiIiuOaaazh8+DDxIT5c2jaMiZ9sZsibG1ib7OwUvHjLKd5ec5jv92TUKWNHQb7gyp8RAV7kGC0XNEZdSQhIINWYWuMxdptc7jFp06c/E557BS//ADYu+ZwNC+chy86S/R999BHdu3ej17C2hEWE0LdPf3755Zda2SM7lCpP4NHR0cyYMYPQ0FB27drF8uXLsVqruLkRS0Iuparmh+dDVlEW3h7eYinoPBCCpRETFehFtqEORaMEjR5ZcVY/vhD+/PNP7r33XrZs2cLatWux2+1cfvnlyDYzi2f0Y+ezI5naL4HbF23nkZV7ePbb/fyTksf/LdvFgr9O1H7COhSOq4rOLQJZm5zNrtQCl3VHdhUOm4za48xpNaZdB2588Q0CIyLZ9esP/DjndWxWC7Gxsbz22mts376dHTt30LfnQMaNG1er5oYOWaa6r0BwcDAzZswgNjaWo0ePsnDhQkz/SbcWHhbXUl44TqU67xgWRVHYnbObHhE96tm6poEQLI2cpKgADmYaGtoMwUVGwRncdyH8+uuv3HLLLXTq1Ilu3brx+eefk5qayo4dOwDnsuPtg1tz66BWrDuUzZ2DW7P8jv70bRnCrwey6jRnXdOaKxIT5M3IjpHEhfiw4bCOdQezSckxnfuFLsBb402Rraja/fb/CBaAkJhYbnzpLSJaJXJ06z+seuVZRgy9jCuvvJJ27drRrl07PvjkHXx9fFn78x/nbYvDUfMJ3MfHh2nTptG+fXsyMjJYsGAB+fmi63t9UZWH5Vwexc0ZmxkYM7Be7WpKCMHSyIkP9SEtv/rS34KmieICD8t/0ev1AISEVI5bee7qjux+7nJmXtkBD7WKOwa3ZsepAt5ec7hW49e2+eG5CPPTMiwpkuEdIlFJEusPZbP+UHa9Lhl1C+/G7sw97P49la9mb2PDkkMc3ZZNkd45p8Mmo/E4+z36BgUz6fnZtOzWk9OHkln+3OMYcnTO1zgcLF++nOKSYnr36FtlgbmqsBaaz/lpenp6MnHiRHr16kV+fj6fffYZp0+fdu50M+9UY6dy88PyQizVHp9VlIWPhw8BngEXw7wmgQi6bQK0DvclJcdEYvjZvUcETRNXCxZFUXj44Ye55JJL6Ny5c43HjugYSd9WIXz8ZwqPXN6+FrPI9Zbd0yrMl1ZhviiKwr7TevadLkStUtE7IRhfretOc3knijkwz0xAQBZdL4slP6uInWtOsXbBAYIifbCaHdVeozy9fbjm8edYO+8DDvz5O2/eM4N3fl6PxWLBz8+Pb775hktG9KmywFxVyA6lSnH0X9RqNWPGjCEgIIANGzawcOFCEhUvsSTkYioVjjvHsWVLQSIrqHbU6nbno48+omvXrgQEBBAQEMCAAQMqBYo5U/bO/nnzzTerHXPhwoVVvqZODb2aKW0i/EnRXRyXuMA9kHGtYLnvvvvYu3cvy5YtO6/jI/y13HpJq3MfWAFXe1iqQpIkusYGMSwpkoGJoexJL2TdwWy2HM/DfoE9uIr0Fn6Zt5/Q3iomzuxNx0tiuOT6tkx6ui+3vnUp/a9JpFXXMDoNblHtGGqNhlF3P0D/627AT3HwyKjBrF78BXfffTc333wzycnJBEX6EBztw/HdOTXG6NTGQSJJEkOGDGHcuHHY7XaOKjr2nTxYm7cvOAdVeViqE+j/ZPzDoJhBF822pkKtbj3KAsXatGkDwBdffMG4cePYtev/27vz+Cjq+3/gr5k9s9krm81uEhIIIeQCwn0E5Iwcikg9QRShYq1tbWur1oInWMWrVm39Un8VRGsVahEVFQTCfUqAcCZcSQgJyW7O3SSbY4/5/bFkQ8hBNjt7Je/n47EPkp2Zz3yWyey+93O8P8cxaNAglJS0XtF08+bNWLJkCe65555Oy1UqlTh3rnXzslQqdadqvV60OgRFVRbEhMn8XRXiAxw8nyXU7Le//S2+/fZb7NmzBzExMV06RixkESp2r+WCg2/zp4gELMYPcGaDrmmwYu/FcjgcHPRKKQZFK92qi8PBYduas4hJCsOQ2zW4YLqAJE1L65I0VIT4YRGIHxbRSSlODMNgwv0PQaHRYvtH/4dLm/6LhY//HkeOHMF7772HDz/8EPIwKYRiAS5mGTFgpK7dZTgYBqhtcmDDn/YCcOZ3YdA6MS5zbf4ywzCubSn2CShqvIoth/ehQclh4sSJlICSB12dJVRSW4JQUSgUYoUvqtWjuPWOM2fOnFa/v/rqq1i1ahUOHTqEQYMGITIystX2b775BlOnTkV8fHyn5TIM0+ZY4p7BfVTYeqaUApZeguPg8VpSHMfht7/9LTZu3Ihdu3ahf/+ut5gIWcb9qc3dXPyQDwqpCFOTdACAUlMDduQawTBAQoQCfcNvfs/kHS9D5dVa3P6rdIilQlwoah2wdEfarbMQGhaG7959E5s/eAcmowGN1wWM0lAR+g/V4sIRQ7sJ5uJu6YNxpiY47A5wnPN6chwAzhkctjzHOH93AAAHNadERbYNHNOAHTt2oKamBrfddhtYloY0eqKlNYzpsGWM4zicLD+JmXEzfVexHqTbnbt2ux1ffvkl6urqkJ7eNuGNwWDA999/j08++eSmZdXW1qJfv36w2+0YNmwYXnnlFQwf3vk0r8bGRjQ2tgyuM5tppoxWIYGxpgE6BbVO9XQc5wwaPPGb3/wGn3/+Ob755hsoFAqUljpn/qhUKoSEhHR6rKA7AYsXx7C4I1IlRaTKeY+cN9QgM8cAhgGGx4YhLFTcal+71YHDm/JwamcRxt+T0K0U+u1ZtmwZbrvtNsTGxmLIvEV48/mlOHr6LO69dSocDrtrNWmhWICBo/W4dNSIvoNaJ5iTKMUY+kD3gqazT+YjIyMDu7O/w5EjR1BTU4N77rkHIpH7CeyIk8PhcA1paHbj3/v+q/upK8gDbofUp06dglwuh0QiweOPP46NGzciNTW1zX6ffPIJFAoF7r777k7LS05Oxtq1a/Htt9/iiy++gFQqxYQJE3DhwoVOj1u5ciVUKpXr0bUVSgMXH/kkhseqkV1Y7XllSMDjo4Vl1apVMJlMmDJlCqKiolyP9evX3/RYAcvA7ubfrC/GsLgrUa9ARooeUxJ1yCuvQ2aOAXsvlKHBasfVi9X452934eJRI+5/bjSGTGlp/VBJVKhuqO72eQ0GAxYuXIikpCTMf+RRNCg0ePLOWRAW52HTOythbWr5MsayDBJG6VB8vhp11fzNgFIoFFiyZAmio6ORm5uLTz/9FBYLzTjsruZlGxhc935+XcBytfYqFGIF5GKaHNFdbn9dSEpKQnZ2Nqqrq7FhwwYsWrQIu3fvbhO0rFmzBg8++OBNx6KMGzcO48aNc/0+YcIEjBgxAn//+9/x/vvvd3jc0qVL8cc//tH1u9lsDvKgxbOF4QBnNK8KEaHa0gS1THzzA0jQMlgEMHqYNNCTIFnIsth04irOXG3bsml3ODBQp8C80bFwXOumcHAcqk1WyGvM4MCgoNyCOG0oRvbzfYr9dnEc4kQiCLUSVBgs2LrpIq5sK4YyToH5fxwBkbh1d8yg8EE4XHIYE/p079vy6tWr2zxnMVXjq9eX4+KRQ/jyledw159eRIjCOeWVYRjED4tA4dkKWBvtUOv56fqVy+VYtGgRvvzyS1y8eBFr1qzBQw89BLVazUv5vYnD4eiwW83BOXCq/BR1BXnI7YBFLBa7Bt2OGjWq1UCxZnv37sW5c+e69E3tRizLYvTo0TdtYZFIJJBIJG6XH6g4zvO05YBzRdttZw2YMYjGBPV0/sy/s3h8HJIj2x80eDCvAmsPFOCrY0VgWQYswzgzsnJWCAXHwTIMrpqcwVb+ytv92k3U1GDD3vXnUXCyAg11VjAsA2W4FKFqCSbNS0TUsHDsy68Ax3Hoo5Yh6dprFrJC2Dk7r3WRqdSY99JKbHr3deQfz8IXLzyDe5Yth0rXci/3TQ1HycVq2Kx2aGP4GbQpkUjwwAMPYNOmTcjOzsZHH32Ehx56iMYVusnVwnJ9HpZr9hfvxy19bvFTzXoOjztkOY5rNZYEcH57GDlyJIYOHdqt8rKzszFkyBBPqxZkOPCRtpxhGMjEQtQ12njNP0ECS4TMjnHx4X47f5w2FHHa9hdenD+mL96b33YMWkXFHmg0zhkp5bWNGPWX7Wi0OSDt7mrFHigrrEFedhmytxfC1uTA3D8MR/RANTiOg+CGFaqnqp3jea5UWpCZYwDHAYP6KMEyLOwOOwQsf/UXSaX42TMvYPtHH+DUjq34/PmncfefX4Y+PsG1T1SCGmWFNSi5ZELUAA/Wn7nu7UYgEGDu3LlQKBTYu3cv1qxZg/nz5990wgRp0dzC4mwob5nWXFxbDLVEjVARvwuV9kZu9UEsW7YMe/fuRUFBAU6dOoXnnnsOu3btwoMPPujax2w248svv8Sjjz7abhkPP/wwli5d6vp9+fLl+PHHH5GXl4fs7GwsWbIE2dnZePzxx7v5koKVg5e05QCQPiAcBy9V8FIWIXxqbk1pDlIabZ7lRumuA19dRO7BEsx6bAh+vWoqYpLCwLJMm2DlerEaGTJS9MhI0aGyrgkVFTp8emwfzA1WXuvGCgSY/thvkX7vAlhM1Vi/fCkKso+22ieirwIhchGunOUv1T7DMMjIyMDs2bNhtVrx2Wef4dSpU7yV39O1BCwtkSAHDqfLT2NIRG/7Au4dbn1CXj9QLCMjA4cPH8aWLVswffp01z7r1q0Dx3F44IEH2i2jsLCwVb6W6upqPPbYY0hJScGMGTNQXFyMPXv2YMyYMd18ScGJ43HKp4BlIBQwaLDy22RNCF9CRAJEKqVY8K9DOHCx3Ofnd9g5jJsbj36Dw93ukmIYBoOiVZiblog4HZBbUoMduQYcuFiOJp4CMIZhMP6+BZjxy9/B1tSIjW+uwOld21vt09UEc+4aPXo07r//frAsiw0bNuDAgQO8ld2TXd8l1Hw5DpUcxsQ+E/1bsR7ErT6D9gaK3eixxx7DY4891uH2Xbt2tfr9b3/7G/72t7+5U40eir8WFgAYP0CL/RfLMTVZx1uZJIAEeVp1Acsg86nJ+OvW83hr6zl8NcD9wMETnINr9U24uwQsgzF9nSn0LU02HMqrgNXugCZUjGGxao9f05BpMxAaFoZNf3sdP656F7UV5Rh79zxXua4Ec0eNGDCi/QRz7WlqkKP8Si0GDG///SElJQUPP/wwPv/8c2zduhVmsxkzZsygXC2dcE5rvtbCci1iCZOqIRNRbiy+0F9fgHBO+eSPWMjCwXEepyMnxFtCJUL8asoAXK2ux6rdl3x6bgdPAUtESASMFucihjKxEJMSI5CRwu9K0vHDR2PeS69DplJj/38/w/Z/fQCHvaX1VBoqQv80LS5mGWBzo1WVFXT++vv27YslS5ZApVLh0KFD2LBhA2w2W7dfR0/HcRxYhgHDtszASwlvm/KDdB+NygwYHK8tLICzleXApQpMSrx5unASZBigut4Kw3VTm5kbtrf8eH0iq7b7tkp01er59sto9WP7T7dbptXetlkoQiHBmsWjMe/DQ+ijDsHcYR2vw8MnzsF5nMcGAJI1ydhXvA86ma6lW4YDwmViTEl0tl7kl9Uh82wpwDkzUmvlEtd+HFqOue6f1i1oDKCNjcf9L76Br99ajpOZW1BbVYnZv3sG4msJ/oRiARJGtZ9grj1iaS000TcfBBoREYElS5bgP//5D86cOYO6ujrMnz+flk5ph8PhgFAgBMsyMDU5Vz4PhESJPQkFLAGCzzEszULEAjTaHHDw9OZMAgcTFoYvV/0PX/q7Im4QcA5wbJYzgGle9+batmQO+Ozvp8ENakQXFiD2mMk4CFv+ZQJz3ey8VuFUm9iqo/vH+fxJ7OjSeXPdqGN7OMedYARfI+/YT/jHkt9CLP8ZGPb6rMTNCctw7bU1V5G7rrYcHA4ZBMKu/UcrlUr8/Oc/x/r165Gfn+/K1aJUKj18NT0Lx3FgWBZXG4ohZJo/Wul9l08UsAQMfsewNBsbr8Gh/ArXInCkZ1j1yhJwN34rR+tkcK2fv+7n67Z0NFazK/u7e96y6nzUN1ZCIR8CB8fBmdnf+a+D4xAiEqBfuG+mfjbUWVFf0wSgnW/B1y0e2PxLmy/Krn0YHDUcxdCIoRAJWn9IuY5p1SLl/MXmcCC7sBr1VjtkEiGGxaogFLDOlqx2PuM4jnO2yHBAU8MkbP/XO7h8MgsS8de4/bfPQxGud+3HccDVC9WQqyWQa6QtLTnXjncODgU00V3PuCqVSvHggw/i66+/xunTp125WnQ6GiPXzOFwAAxwsfY8ZEIZqvxdoR6IApYAwfcYlmZKqQi1DTbXCHbSMzhnI7S7xddV6TJVSCIslgLU12chXDvZr3WRhoogDeVn3ZxR8qE4V3UOI7Uj3TpuktqZmK2mwYqsy1VdXklaphTj7j+/gMw1q3By+xZ88/ZzuPvZlxCZkOjaR62T4erFajjsDt4SzAmFQtx9991QKpU4cOAA1qxZgwceeAD9+vXjpfxgx3EcikVFuC/iQezDfgDtBLrEIzToNmB4npq/IyP7heFYIcX7xP9ksjjI5SkwGrfwOhXXn+RiOeqsdd0+vnkl6YwUPbRyCXbkGrEj14DCio4zGbMCAW599DeYMG8h6s0mrF+xFHnHj7TaJzpBDc4BlOaZul23NudlWcyYMQMzZ85EQ0MDPv30U5w9e5a38oOZmTVDxslazwqiiIVXFLAECA4cGC9djnC5BBW1TV4pmxB3SSQ6aDQTYDBsgsPBb9K1YBepkiIjRY9pyXo02OzIzDFgR64BVXVt71+GYTDu7nmY+asn4bDZ8PWbr+DUjq2t9onoq4A0VIQrOfwlmAOA9PR03HvvvQCA//73v/jpp594LT/Y2B12VImqoOP0YFmmw65W4hkKWAIF5/BaCwsADIlR4WRRtdfKJ8QdQqECOt0sGI0/wGbrfutEoIhRxOCK+QqvZXa2kvT1Bk+5FXf96UUIxRJs/fB9HPjyP61ar9R6GcIi+U8wN3jwYDz00EOQSCT44YcfsH379h7TauauPUV7oLfonV21LFyDt/hYH460oIAlQHDgZ/HDjkSpQlBq8mx1X0L4xLJi6PVzUFG5G01Nvs92y6f+yv7IN+d7pWyWZTCyXxgyUvQYHafB0ctV2JFrQFZBJRzOkcuIGzYS815aCZlKjYP/+wJbP/x7q1wt8jApogeqcfGo0XUMH/r3749HHnkECoUC+/btw9dffw27vXdl2L5svowIaQSEnLAl022rGVqELxSwBArOAW//dSdFKpBbavbqOQhxB8Ow0Otuh9l8CvX1/LZQ+JKvBrRLRQJMSNBiWrIeCTo5dl8ow45cA86V1kAfn4AFf3kbYdExOL1zK75+6xU0NdS3HHstwdyFI+4lmLsZvV6PJUuWICIiAidOnMDnn3/eZkHcnsrusON81Xkka5IBAAxaryVEY1j4RQFLAPHGtObr9QsP7XQgHyH+otVORUPDVdTWnvN3VbotRBgCi9V395daJsbUJB2mJeshEwuQmWPAkXIG055egajEZOQfz8J/ly+DxVTtOkYoFmDgKB3ys8vRWM9f1lq1Wo2f//zn6Nu3Ly5duoS1a9eipqaGt/ID1d7ivZjYZ6JzSjOcrWEMw3ScL4B4hAKWAOGc1uz9y9FfG4r88uAfM0B6nrCwsXA4GmEyHfd3VbpliHYITpX7Z3Xj61eSrmMkiLjv91ClDIch7wI+f+FpVJUUu/ZlBSwSRulQfK4KddX8tYTIZDIsXLgQKSkpKCkpwerVq1FeHtxdfZ0pMBVAL9NDKpReN3aneQyL6zd/Va9HooAlYDh80qw8UK/ABUPP/+ZDgpNSmQahUIHKyv3+rorbpEIpGu3+7QppXkl6elosHn7uRUSNy4DJUIpPlz2NwtycVvvFD4tARXEtqg38tQqJRCLcd999GD16NKqrq7FmzRoUFRXxVn6gsDlsOF91HinhKQDgamFhGKZ1VnHqEuIVBSwBwlctLAAQrQ5BcXX9zXckxA9CQxMgk/VHWdm2oJx1Eih1FotEeODJJzFxwWLYLDXY8Jfn8NXXP+J4YZWrjn0HhcNS04TyIv6+xLAsi9tvvx233norLBYL1q5di3Pngrerrz17i/ZiUswk1+/N/5/NqzU3D7qleIVfFLAEDN9loh3cR4UzxfwlkyKEb1JpNNTq0TAYvwPHBc+skwR1Ai5WX/R3NVwYhsGYuffitieeAhx2FKz7AJaT+1qtJN2cYK7kEn/vCQzD4JZbbsFdd90Fh8OBdevW4ejRo7yV70/5pnxEyaMgFbYsAOlqYQHjHHQbIEFrT0MBS4DwxuKHnQmXS1BW0ztG8pPgJBKpEaGdDoPhO9j93NXSVdHyaJTUlfi7Gm2kTpyKu/+8HCKpBIf+/SEkJ7ZiWrIOLMNgR64BpywWWODgPcHc0KFDsWDBAohEImzatAm7du0KmBao7rA5bLhYfdE1K6hZSwuLc8mMlpdITSx8ooAlYHhn8cOOjOirxnFK108CnEAghV5/B8rKt8JqpVZBT/RLG4Z5L7+B0DANDn21Hj+ueg991RJMS9ZjapIOdRIGZ2st2LT5Euoa+ctAnJCQgMWLFyM0NBS7du3Cpk2bgjZXy56iPa26gppdP4bl+mnNtH4bvyhgCRCcD/KwXI9hGChDRDDVU2p0EtgYRgC97g5UV/+EhobAa724kUKsgLkpMPMd6eLiseCVt6HpE4szu7fj6zdXoKneAoZhkBajxszRMZgyIQa7tl/G9jOlOJRXAZvd84VZo6OjsWTJEmg0Ghw7dgzr169HU1NwLReSZ8pDH3kfSASSNtu46zLbsgwDUOI4r6CAJWBwPm1hAYAxcRr8lM9vEzAh3sAwDCIipsNiyUNd3SV/V6dTg7WDcbrstL+r0SFlhA7zV7yJPsmpKDhxDOuXL0VddUtrq0Ipwczp/RFbCyRHyLH3Yjkycww4XWzyqDtHo9FgyZIl6NOnD86fP49PPvkEdXXBkWLB6rDiUvUlJGmS2t3euoUlcAZe9zQUsAQIX7ewAM4kR1IRC0sTfwmkCPEmjWYCbDYTzGb/5DvpChErgo0L7HsqRK7Avc/9BQPHjocx/xI+f/5pVF5tmX7cnGCuLLca4/tq3FpJujOhoaFYtGgREhMTUVxcjNWrV6OqKvC7pvcW7cXkmMkdbm+dh4WhPCxeQgFLwOC8uvhhR9Ljw3HwUoXPz0tId6lUI8CyYlRVHfZ3VTrEgIGD87wrxZuEYjHuePJZDL9tDsxlBnzxwjO4er4lV4srwVyuM8GcOytJd0YsFmPevHkYMWIEKisr8dFHH+Hq1at8vzze5FU7u4LEAnGH+7RqYWEoD4u3UMASILy9+GFHhAIWLMug0Racg+BI7ySXJ0EqjUJ5+U5/V6VdKeEpyKnIufmOfsayAkxd9BgmPfQIGmpr8OWK53DhyEHXdoZhED/8WoI5Y0urSldXku6IQCDAnDlzMGXKFNTV1WHt2rW4eDFwpoM3szqsyDPlddgV1MyVmv/al07X4oeEVxSwBArOt7OErjd+QDgOUCsLCTIhIX2hUA6BwfjDtS7VwKEN0aKiITjuKYZhMHrO3bj9d8/A4XBg019XIvvH71vt03dQOCzmtgnmurKSdGfnnTJlCubMmQOr1YrPP/8cJ06c4P31eaKjWUE3un5a87UnWv9OeEEBS4BwRuT++eOWCAVwODheZgMQ4ksSsRbhmskwGDbB4QiuWSeBJmXCZNyzbAVEUiky16zC3s/Xtho82pxgrjSv/enlna0k3ZmRI0di/vz5YFkWGzduxL59+wJi0Oql6kuIVcR22hXUrKVL6NpHagDUvyeigCVQ+Dhx3I3SB4TjYF5wfCMk5HpCYSh0utthNG6BzVbr7+q4hEvDUV4fXIv/9R2chvkr3oRcE46fvvkftnzwDuy2ltQHEX0VkMiEN00w195K0tvPGlBian9JkKSkJCxevBghISHYvn07Nm/e7AoC/MHqsKLAVIDEsMQu7d+mhcX5izeq1qtRwBIwfLP4YUdkYiEarI6bNuMSEohYVgS9fg4qK/ehsbHM39UBEDzjWG4U0TcOD7zyNsJj+uLs3p346vXlaLS0jF8JiwxFWKQMedllXWoJuX4l6cq6JmTmGLDznBHmhtY5oGJiYrBkyRKo1Wr89NNP+PLLL2G1+idPVFe7gppdP+gWAI1g8RIKWAKELxc/7MiY/hr8VEB5WUhwYhgGOt0s1NSegcVy2d/VAcuwQTv4UqmNwPwVbyImdTAKT2Vj/cvPoraypQVWHiZF9EA1Lh41dvlLTvNK0hkpekxM0CK3pAY7cg04cLEcTTbnB75Wq8WSJUsQFRWFnJwc/Pvf/0Z9vW8Xar1YdRF9FX0hEoi6fEx7Y1hoSjP/KGAJEJwfEsfdSBUigrneGhD9x4R0lzZ8ChobDaipzfV3VSBkhLA6gjObtDRUjnuWvYLE9Ikou5yPz194GhVFV67bLkL/NC0uZhlgt7rXfSMUsBjTX4NpyXoM66vGobwK7Mg1IPtKNeRyORYvXowBAwagsLAQa9asQXV1Nc+vrn1WuxWXzZcxMGygW8fdOEsIAGW59QIKWAKFHxLHtWdEvzAcozWGSJALCxsDjrOh2uTfFYIHRwzGmfIzfq2DJ4QiEe743TMYOftnqCkvw7oXn0FRbsvrEYoFSBipQ152GRrru5csTyYWYlJiBKYl6xETFoKd54zYl1eNsdPvRFpaGsrKyrB69WoYDAa+XlaH3O0KanZjCwvHcTRDyAsoYAkYgfEHrpVLUFFLsy1I8FMqBkMkDENF5T7/1UGsDNh1hbqKYVlMefhRTHn4UTRY6vC/vzyP84f3u7a3SjBn8mxVba3cuRhjRooeIqEQqpTxiE0ZjpqaGqxZswb5+fmevpwOXai6gDhVnFtdQc1uHMNCvIMClgARCGNYmg3uo8LpYloZlwS/0NB4hIYmoKxsK3V1emjk7J/hjt//CeA4bPrb6zi2+VvXNleCuaLWCeY80V8bioyUSDxy/50Ymj4FjY2N+PTf/8ax7JO8lH+9JnsTCmsKMUA9oFvHt9fCEggt5j1NYHxCEvhj8cOORKtDcLXatwPdCPEWqSQSavU4GIzfweHw/Ro/UaFRuFobuKnn3ZGUPhH3PPcKJDIZdq79f9j92Rpw100/bkkwx9/0coZhcNfMKbj//vvBMgy+/forfPrNNt5Wkga63xXUrE0eFtCsZm8IjE9IElAtLAAwUK/AeUPnCZ8ICRYikRIR2hkwGr+H3e7bYDxBnYCL1YGXdr67YlOHYP7yNyEP1yJr01f44R9/he266cfOBHNchwnmuis1NRUPP/wwpFIp8o7vR3nuEey5UObxStLnKs8hXhUPEet+V1Cz5nOz12e6pYiFd4HzCdnrBcYYlmb9taEoKA+Opd8J6QqBQAK9/g6Ul2fCavXdwPJAuq/5oo3thwV/eRvavnHI3b8bX618CY2WlveLriaYc1e/fv3wyCOPQKlUIuunQ6g6sw+TB4a3Wkn6SmXXu6Sa7E0oqi1CvDreo3pRHhbfoICFdKhfOAUtpGdhGAF0utmoNh1DQ4PvumkkAgkabA0+O58vKDRazF/+BmIHpeHKmZNY99KzqKloyewbFhkKtb7rCea6SqfT4dFHH4VOp8OpU6fwn//8B2oJXCtJ11vt2JFrwM5c401Xkva0K6hZe6n5KQ8L/9wKWFatWoW0tDQolUoolUqkp6dj8+bNru2LFy92La/d/Bg3btxNy92wYQNSU1MhkUiQmpqKjRs3uv9KCO+SIqlbiPQ8DMMgQpsBi6UAdXW+6aoZoh2CU+WnfHIuX5LIQnH30uVInjAZ5YUF+PyFp1F+pSVpn0LTkmCO4zGLtlKpxM9//nPExcUhPz8fH3/8Mcxm52ysRL0C05L1mJwY0elK0ucqzyFe7VlXUDPXoFuWUvN7k1sBS0xMDF5//XVkZWUhKysL06ZNw9y5c3HmTMu8/FmzZqGkpMT1+OGHHzot8+DBg5g3bx4WLlyIEydOYOHChbj//vtx+PDh7r0iwqsoVUiH638QEsw0mvGw2WphNvM/6+RGMpEM9baeeR8JRSLc/sRTGH3nPaitKMe6F/+EK2dbgrPmBHMXupFgrjMhISF46KGHMGjQIBgMBqxevRplZS3LMnS2knS9tQHFtcWIV3nWFdSsbeI46hTyBrcCljlz5uD2229HYmIiEhMT8eqrr0Iul+PQoUOufSQSCSIjI10PjUbTaZnvvvsupk+fjqVLlyI5ORlLly5FRkYG3n333W69IMKvITEqnCqiKc6kZ1KphoFlJaiqOnTznXnQU6dWMyyLSQ/+HFMX/xKN9RZsePUFnDu417W9OcHcpWxjtxPMtUcoFOKee+7BuHHjYDKZsGbNGhQWFrbZ78aVpP955DvY65JvupJ0V7U7rZkaWHjX7TEsdrsd69atQ11dHdLT013P79q1CzqdDomJifjFL34Bo9HYaTkHDx7EjBkzWj03c+ZMHDhwoNPjGhsbYTabWz2Id4TLxaio9SwhFCGBSi5PglQag/LyHV49T39lf+SbvZf4LBCMuG0O5vzhzwDD4Lt338DR7792bWMFLAaO0vOSYO56LMti1qxZmDFjBurr6/Hpp58iJ6fjRSdLG/Lws0EjMT0lGjKxAKt2XfI471SbxHEcaAyLF7gdsJw6dQpyuRwSiQSPP/44Nm7ciNTUVADAbbfdhv/85z/YsWMH/vrXv+LIkSOYNm0aGhs7/uMsLS2FXq9v9Zxer0dpaWmn9Vi5ciVUKpXrERsb6+5LIV00om8Yjl6mdP2k5woJiYFSORQGw/fXUgzwL1YZi6KaIq+UHUgSx07Avc//BdJQOXZ9+hF2ffovV64WbySYazZ+/Hjcc889cDgc+O9//4sjR4602afR3oiS2hIoBdHIzDHgvKEGd6RFYXAflUfnbrP4ofMXj8okbbkdsCQlJSE7OxuHDh3Cr371KyxatAhnz54FAMybNw+zZ8/G4MGDMWfOHGzevBnnz5/H999/32mZN07768o6DEuXLoXJZHI9rly50un+pPsYhoFcKmyzHDwhPYlYHA6tdioMhk1wOKhF0RMxyYMwf8VbUEbocPT7b/Dd+2/B1tQyY6fvoHBYTPwmmAOAIUOG4KGHHoJIJML333+PzMxMVzDRZHPg/x35DtbaJBRWWjAtWYeMFD1iNTKPz3vjLKFgXaU70LkdsIjFYiQkJGDUqFFYuXIlhg4divfee6/dfaOiotCvXz9cuHChw/IiIyPbtKYYjcY2rS43kkgkrtlKzQ/iPeP6h+NwHr85FQgJNAKBDDrdbBiNP8Jm43+GnEwoQ20Tvx/SgSo8JhYPvPI2IuLicf7gXmx47UU01La89uiB3kkwFx8fj0ceeQRyuRx79+7F2i++xLYzV/HfU4cwPWE4ZqRGY3jfMF7z47RpYeE4amDxAo/zsHAc12GXT0VFBa5cuYKoqKgOj09PT8e2bdtaPbd161aMHz/e06oRHrEsA4mQRX2T/eY7ExLEWFYIvX4OKisPoLGR3xWCh0YMxcly789KChTyMA3mvfQ6+qUNR1HOaax76U8wl7fM5PFWgjlWpkbKlJ8hRKHG5fNnUXTsR+hUtUjW8jMr6EZtEsdxAI265Z9bAcuyZcuwd+9eFBQU4NSpU3juueewa9cuPPjgg6itrcXTTz+NgwcPoqCgALt27cKcOXOg1Wpx1113ucp4+OGHsXTpUtfvv//977F161a88cYbyM3NxRtvvIHt27fjySef5O1FEn6MHxCOA5fKb74jIUGOYRjodDNRW3sOFgt/A2VFAhFsfljPyJ8kMhnuevZFpE6cioqiQnzx/FMou9zyf9qcYC7/hGcJ5hqsduy9lqq/1NyA20cOwG9/9RhiY2Oxv2Q/8rbnobbWO61bLS0s168lRAEL39wKWAwGAxYuXIikpCRkZGTg8OHD2LJlC6ZPnw6BQIBTp05h7ty5SExMxKJFi5CYmIiDBw9CoVC4yigsLERJSYnr9/Hjx2PdunX4+OOPkZaWhrVr12L9+vUYO3Ysf6+S8EIoYMEyDJps3hmUSEigCQ+fhKamCtTUnOW13J46vbkjAqEIs37zR4z52X2orarEupeeReHpE67tCo0UUQPcTzDHcRxOFlUjM8eArIIqjI7TICNFj7QYNRiGgUwmw+g7RmNEzAiUXi3F6tWrUVFRwfvra8nD0hyk9K7r6ysM10PuHLPZDJVKBZPJFJTjWSoq9iA83PMU0d7WaLPjwKUKTE3S+bsqhPhMTc1Z2O0WqNWjPC7LaDGior4CKeEpPNQs+GRv/QE71vwTDMti1m/+gJQJk13brE125GeXYcBwHQSijr9Pl5jqcabYDIYBhvRRQaeUtrtfva0eh0sOY1KfSfjhhx+QlZUFmUyGBx98EH369OHtNe3fvx/btm3D5LEzMPW28fh/v/k5muoteGLNet7O0ZN19fOb1hIibpEIBbDbOdh5TLNNSKBTKFIhFoejomKPx2XpZDqU1ZfdfMceatiM23HnU8vAsix+eP8tHPl2g6vFSdRJgrn6Jjv2nHd2+VTWNSEjxTnLp6NgBQD2Fu3FxD4TwbIsZs+ejWnTpsFisWDt2rWdTgZxV5s8LKA8LN5AAQtxW/qAcBy8xH+zKiGBTCbrD7k8CUbjj72uS4dvCaPH4b4XX4VUocSe/3yMnWv/HxwO54D+6xPM1VY34HhhFTJzDDhWWIVx8eHISNFjULTqpmNEzlScQbImGQJWAMAZTEyaNAlz586FzWbD559/juPHj/PyetoufgjKw+IFFLAQt4VKhLA02ehNm/Q6EokeGs34a7lauj94Vi1Ro6qhdydjjE5MwQMr3oRKp8fxLZvw3btvwNrknHFaVFWPfKkDOw4VI8zBICNFjwkJWoiFXfvIslgtKLeUo6+yb5ttw4cPx4IFCyAUCvHNN99g9+7dHr+XNR/fPIaF8rB4BwUspFvG9g/H4XzKy0J6H6FQAZ1uJozG72G3dy9b66DwQThTcebmO/ZwmugYPPDK29D1H4ALhw9gzXN/xo9HL6GuyYaMFD3unDUAYitQUeze7J59xftwS59bOtw+cOBALF68GDKZDDt37sT333/vaiXpjrYtLBy1sHgBBSykW1QyEUz1VmplIb0Sy0qg189BeflONDW53z0qYAVweGkJgGDicHDIqeagn/8HqAcOQW3hBVz9z9uIFjS49okeqIbD3vUEc2fKzyBFk+LqCupInz598OijjyIsLAxZWVlYv349mq7LxuuO9lLzU7jCPwpYSLeN6BuG41eq/V0NQvyCYVjo9bNhNp9Afb37awSxDNvrcrI0KyivQ2aOAbvOG5Ggk2PGsDgsfvkVDJp8KyqLr+DzF56GsSDPtb8rwVxu5626FqsF5fXliFV2bW05jUaDJUuWIDo6GufOncOnn34Ki8X9VrO2ix/SFzlvoICFdFuEQoLyGlpzhfRuWu001DdcQW3tebeOGxw+uFd1C5kbrNiZa0RmjgE2B4eMFD2mJeuhlokBAAKhEDN/9XuMu2c+6qoqsf7lZ1FwsmVQbFhkKNS6zhPM7S3ei4kxE92ql1wux6JFi5CQkICioiKsXr0aVVXujS+6sYXFmeiW2lj4RgEL8UhqtNLjpdkJCXaasHQ4HA0wmbK7fIxaqoapsWffO3YHh8N5FcjMMSDnqhmTEiOQkaJHgk7e7v4Mw2DC/Q9h+i+egLWhERtffxln9+xwbe8swdzp8tNIDU8Fy7j/sSaRSPDAAw9g+PDhqKiowOrVq1slOL2ZlsRxLWNYKNMt/yhgIR6JCZPhanW9v6tBiN8plWkQCENRWXnA31Xxu4vGWmTmGLDnQhlSopXISNFjbHw4BGzXPsTTbp2Fuc88B1YgxOYP3sHhr790tWJI5SLEpWlx/ogBdqszULBYLahsqESsomtdQe0RCAS48847MWnSJNTW1uLjjz9GXl7ezQ9E+2NYCP8oYCEeS9DJccHA/8q2hAQbeehAyGRxKCvP7NKAdJ1Mh9K60pvuFwyqLU3YkWtAZo4BQtY5FXlqkg5Kqahb5Q0YORb3v/gaQhRK7PviE2Su+acrV4tILMDAUc4Ec031tpvOCuoqhmEwbdo03HHHHbBarfjss89w8uTNF6tsu/ghjWHxBgpYiMfiI+TIL6/zdzUICQhSaTTUqhEwGr8Hx3W+unlSWBLOV7k39iWQWO0OHLzk7PK5VFaLKYnO7LNx2lBeyo8amIQHXnkLan0UTmz9HpveWenK1dKcYC7z2AH0Fyd0qyuoI6NGjcK8efPAsiy++uor7N+/v9MghBY/9A0KWAgv+obLcLmCghZCAEAkCoNWmwGD4TvY7R0PTA/WD7XcUjMycwzYf7EcaTEqZKToMbKfBmwXu3zcERbVBw+88hb08QNx8cghfPnKc6ivMQMALDYLQvsB4ioVTGXdy4nTkeTkZCxatAghISHYtm0bfvzxxw5ztbTbwhKk1zaQUcBCeJEcqcS5UuoWIqSZQBACnW42ysp+hNVq7nA/IStEk717+T98qaK2EZk5zi6fULEQGSl6TEnSIVQi9Pq5ZSo15r20Ev2Hj0LJ+Vx88cIzMBlLXV1B/QaFo666CeVF7iWYu5nY2FgsWbIEKpUKhw4dwoYNG2C1WtvsR3lYfIMCFsIbvVKKUlPDzXckpJdgWSH0+jmorj6Ehsb2x6oMjRiKk2U3HyfhD002B/ZfLEdmjgGFlRZMS3Z2+cRqZD6vi0gqxc+eeQFDps1AVUkxPl32JPrUKV1dQc4Ec44uJ5jrKq1Wi0cffRSRkZE4c+YMPvvsM9TXt55oQHlYfIMCFsKbobFqnCyq9nc1CAkoDMMgImIG6movoK6u7ayTUFEoLDZ+uzM8wXEcThebkJljwKG8CozoG4aMFD2G9w3zexcWKxBg+mO/xci77kVTTS12vPkOCrKPurbr+im7lGDOXQqFAosXL0Z8fDwuX76Mjz/+GCZTS2B0Y2p+ysPiHRSwEF6FhYpRWRf4zduE+Fp4+ERYbVUw15z2d1XaZTQ3IDPHgB25RoTLxchI0WNSYgRCxJ2nuPc1hmHQOC4K0x/7LWxNjdj45gqc3rXdtb0rCea6QyqVYsGCBRgyZAiMRiNWr14No9EIoO3ih9cqytu5iRMFLIRXo/qFIauAFkUkpD1q1UgwEKCq+kir5/sq+uKy+bLP69NgtWPvhTJk5hhgMDe6unyiVCE+r0tXZRuzkaZNQ1rGTPzsTy+AFQrx46p3cWjDOlfg0FmCOU8IhULcddddmDBhAsxmM9asWYPLly+3u/ghQ6NYeEcBC+EVwzCQS4SoaWg7MI0QAigUKZCIdSiv2OV6rp+yn88CFo7jcOJKNTJzDMgqqMLoOA0yUvQYEqPye5fPzdQ01aDWWosoeRQAIH74aMx76XXIVGrs/+9n2P6vD+CwO6eSNyeYu5DVkmCODyzLYvr06Zg1axYaGhrw6aefori4GACNYfE2ClgI78bFh+NQHrWyENIRmawfFPJBMBg3g/NRGver1fXIzDFg5zkjotRSZKTocctALaSiwOry6cyBqwcwIXpCq+ciBwzEAyveQlhUNE5mbsE3f30V1gbn4H+RWICEkS0J5vg0btw43HvvvQDgGs/CutYS4miakBdQwEJ4x7IMxEIWDdbOk2YR0ptJJBEI10yEwbAJDocVIcIQWKz8Dr6tb7Jj93lnl0+VpQnTknWYlqyHTiHl9Ty+kG3MxtCIoe0Gd+rIKMxf8RaiEpKQd/QnfPnKc7CYrwUR1xLMXcmtRJ2J38VaBw8ejIULF0IikQAAhMKWrL6B3loVjChgIV4xfkA4Dlwq93c1CAloQqEcOt0sGI0/IDVsAE6Wez69meM4HCusQmaOAccLq5AeH46MFD0GRQd+l09HzE1m1FnrEBka2eE+MqUK9734KuJHjkHJxXP44oWnUV3qXMCQYRgMGK5DeVEt7wnm4uLi8Mtf/hIPPvggpJJrY3+oR8grKGAhXiESOP+0mmz89R0T0hOxrBh6/RzUmg7D0tj9IP9KpcXV5dNPI0NGih7jE7QQC4P/bf7A1QMYHz3+pvuJJFLMfeo5pN06C9WlJfj8hadRerFl6YPmBHMVxfwmmNNoNBg4cKDrd+fg3+AMDgNZ8P8lk4A1foCWWlkI6QKGYaHX3QaLpQAWS9cH39Y22rDrnBGZOQZYmuzISNFjWrIe4XKJF2vrW8eNxzEsYliXW4dYgQC3PvobTJi3EPVmE9avWIq84y2zsqIHqmG38Z9grjWOZjV7AQUsxGukIgFsdg52HqcVEtKTjex7D86WZaG29lyH+zgcHLIKKpGZY8CpIhNuSdAiI0WPpEiFD2vqG6ZGE+qt9Z12BbWHYRiMu3seZv7qSThsNnz95is4tWOra3tzgrkinhPM3VAJ75XdS1HAQrxq3IBwHMqr8Hc1CAkKUfIoWAQRcDgaYTIda7Utv7wOmTkG7D5fhgSdHBkpeqQPCIdQ0HPfxg+VHEJ6dHq3jx885Vbc9acXIRRLsPXD93Hgy/+4crWERYZCpZMh/2Q5rwnmAJrV7C099y+dBAS5RIi6RhvvbwiE9GRKZRqEQhWulOzGzlxnl4/dwSEjRY+pyTqoZWJ/V9HrjhmOudUV1JG4YSMx76WVkKnUOPi/L7D1w7+7crUoNFJExat4TzBHieO8gwIW4nVj+mvwUz7lZSGkK0KFCuw4V4BDhXIU10YgVZONack6JOjk/q6az5gaTWiwN0AfquelPH18Ahb85W2ERcfg9M6t+PqtV9DU4FzAsDnB3Pkj/CWYozws3kEBC/E6tUwMU72VWlkI6cRFY40zX0p1JOziy8hI0WPcwFRowsbAYPwOHNd78hodLDmI9KjudwW1R6WLxAMr3kRUYjLyj2fhv8uXwWKqBuBMMDdwFL8J5oJ1Cnkgo4CF+MSwWDWyr1T7uxqEBJSquibsyDUgM8cAIcsiI0WPW5OjIBG1fNiJRGpEaKfDYPgOdnuDH2vrG0cNRzFCN8IrH/ghCiXue+FVJIweB0PeBXz+wtOoKnGm1XclmMvhIcEcfTfzCgpYiE/olFKU1fCbZZKQYGS1O3DgUjkycwzIK6/FlETngoNx2lDXPizDwu5oaVERCKTQ6+9AWfk2WK3Vfqi1b1Q3VKPJ3gSdTOe1c4jEEsz541IMnTEbJkMpvnjhGZRccM7KYhgGA0Y0J5ir7/5JKA+LV1DAQnwmJUqJs1fN/q4GIX6RW2pGZo4BBy5VYGiMGhkpeozspwHLtv1gS9GkIKcyp9VzDCOAXncHqquPoKHhqq+q7VOHSg9hXNQ4r5+HZQXIeORxTFywGPU1Zvx3xTJcOnrYtd2ZYK7B7QRznOtfjqY1ewEFLMRnYjUyFFXxmxabkEBWXtuIzBxnl0+oWIiMFD0mJ0YgVCLs9LjwkHBUNrQdqM4wDCIipsNiyUdd3SVvVdsvskqzMFI30mdjPxiGwZi59+K2J56Cw27DN2+9ihPbNru2Rw8M8yjBHIUr/KOAhfhUfIQcF438psUmJJA02uzYf9HZ5VNUVY9pyc4un1iNjLdzaDQTYLOZYTZ7vvZQIKhqqIKNsyFCFuHzc6dOnIq7/7wcIqkE2z/6APvX/9s1QUDXTwlxSNcTzLmCFJpg4BUUsBCfStDJkVdGAQvpWTiOw+liEzJzDDicV4mR/cKQkaLHsFh1t1sMwkPCUWYp63C7SjUcLCtBVdXhDvcJFodLD2Ns5Fi/nb9f2jDMe/kNhIZpcOir9fhx1Xuw25yzhTRRzgRzBW4kmHMOYaE2Fr65FbCsWrUKaWlpUCqVUCqVSE9Px+bNziY0q9WKZ599FkOGDEFoaCiio6Px8MMP4+rVzvta165dC4Zh2jwaGnr+aPjeKlYjw5VK6hoiwc9obkBmjgE7co3QyiXISNFjUmIEpCKBx2WnaFKQW5nb6T5yeRKk0iiUl+/0+Hz+cqT0CEbpR/l9GrAuLh4LXnkbmj6xOLN7O75+cwWa6p3vUwqNFJHxKlw6VtblBHP+fj09kVsBS0xMDF5//XVkZWUhKysL06ZNw9y5c3HmzBlYLBYcO3YML7zwAo4dO4avvvoK58+fx5133nnTcpVKJUpKSlo9pFJpt18UCWwpUUrklNDgWxKcGqx27DlfhswcA4w1ja4un0gVv+9ZLMM6B2/eREhIXyiVQ2Aw/gCOC67V0SsbKuHgHNCGaP1dFQCAMkKH+SveRJ/kVBScOIb1y5eirroKgDPBXL/B4V1MMEddQt7Q+civG8yZM6fV76+++ipWrVqFQ4cOYcmSJdi2bVur7X//+98xZswYFBYWom/fvh2WyzAMIiPdW9yKBDedUgqjuQE6JQWmJPBxHIeTRSaU1zZCKhJgbLwGEqHnrSg3I2SEsDqsELGiTvcTi7UI10yGwfAddLpZYNngSN3/U+lPmNlvpr+r0UqIXIF7n/sLfvjH27hw+AA+f/5p3LNsOTTRMRBJBEgYpcOlY0bEDdZCHNL+RyglyfSObo9hsdvtWLduHerq6pCe3n5GQpPJBIZhoFarOy2rtrYW/fr1Q0xMDO644w4cP378pudvbGyE2Wxu9SDBgxLJkWBQXF2P7WedXT5RaikyUvSYkKD1SbACAEMihuBU2aku7SsUhkKnuw1G4xbYbIE/TixQuoLaIxSLcceTz2L4bXNgLjPgixeewdXzzmnmguYEc7mdJJjjqEvIG9wOWE6dOgW5XA6JRILHH38cGzduRGpqapv9Ghoa8Oc//xkLFiyAUqnssLzk5GSsXbsW3377Lb744gtIpVJMmDABFy5c6LQeK1euhEqlcj1iY2PdfSnEz9QyMarqmvxdDUJasTTZsPtal4/JYkVGirPLR6fwfWugQqxArbXrwQfLiqDXz0Fl5T40NnY8YNffKuorwHFcwHQFtYdlBZi66DFMeugRNNTW4MsVz+HCkYMAriWYG65D+ZVOEsxRwMI7hnOz7aqpqQmFhYWorq7Ghg0b8NFHH2H37t2tghar1Yr77rsPhYWF2LVrV6cBy40cDgdGjBiBSZMm4f333+9wv8bGRjQ2tkS3ZrMZsbGxMJlMbp0vUFRU7EF4+CR/V8OnOI7D9hwjpqfys8AZId3lcHA4fqUa1ZYmhIgFGNVPA7EwMCZR7inag0kx7r83lFfsgiwkDjJZHP+V8gDHcfjx8o+YFTfL31Xpspz9u7Hlg7+Bczgw7ee/xLCZs13brl6ogkQmgiY6FFfOVqLvoHD8df4caGP7YdFb//BjrYOH2WyGSqW66ee3W2NYAEAsFiMhIQEAMGrUKBw5cgTvvfcePvzwQwDOYOX+++9Hfn4+duzY4XbwwLIsRo8efdMWFolEAolE4m71SQBhGAahYgFqG22Q3ySRFiHeUFhhwQVjDRgGGBYbBk1omL+r1EYfeR8U1RQhRhHj1nHa8Cmoqj4Cu70eCkWKl2rnviOlRzBaP9rf1XBLyoTJCFWF4Zu3/4LMNatQU1GGWx5YBIZhED0wDMbLZpReMoFpzlrMcZQ4zgs8/grBcZyrpaM5WLlw4QK2b9+O8PDwbpWXnZ2NqKgoT6tGgsDY+HAculTh72qQXqS20Yad54zIzDGgwWZHRooe05L10IQG5kDVeFU88kx53To2TD0aHOyoNh3luVbdU15fDoZhEB7i/meDv/UdnIb5K96EXBOOn775H7Z88A7sNiuAlgRzAuF1YQp1CfHOra+1y5Ytw2233YbY2FjU1NRg3bp12LVrF7Zs2QKbzYZ7770Xx44dw3fffQe73Y7S0lIAgEajgVjsfDN4+OGH0adPH6xcuRIAsHz5cowbNw4DBw6E2WzG+++/j+zsbHzwwQc8v1QSiAQsA5GQRYPVzkvuCkLa43BwOFpYBXO9FaESISYmaCEUBEaXz814OnhTqRgMiyUfFRV7ER4+kadauY/jOGSVZmFW/+DpCrpRRN84PPDK2/hq5Us4u3cnaqurcOcfl0EikyG8j7z1zhSw8M6tgMVgMGDhwoUoKSmBSqVCWloatmzZgunTp6OgoADffvstAGDYsGGtjtu5cyemTJkCACgsLATLtrxRVFdX47HHHkNpaSlUKhWGDx+OPXv2YMyYMZ69MhI0xg8Ix74L5Zia7L0VWknvlFdWi/zyOrAMgxF9w6CSdT49OFBJBVLU2+oRIgzp1vEyWX+wghAYy35EhHaGX2aw/FT6E8ZG+S+bLV+U2gjMX/Emvnn7Lyg8lY31Lz+Lu//8MuQaZ6sRTWn2HrcH3Qaqrg7aCVS9cdDt9XbkGjBxYAREQfKtlwQuU70Vxy5XwcFxiNOGYkCE/OYHBbh6Wz1OlZ3CmCjPvshZrWZUVOyCTnc7WNZ348bK68uRb8rH6MjgGrvSGZvVis0fvIPzB/dCoY3APUtXIDwmFpzDgXceuBO6uAFY+MZ7/q5mUOjq5zd9OpCAMH6AFgdpLAvpJpvdgUN5FcjMMeC8oQaTEiOQkaLvEcEKAIQIQ9Bg93y5EpFIiYiImTAav4fd3sF0XJ41dwX1pGAFAIQiEe743TMYOftnqCkvw7oXn0FR7pmW7MTUI8Q7mppBAoJUJECTzQGHgwPL0p1OuuaCoQZXqixgGAaj+oVBIQ3OLp+u4jjO4+4cgUACvX4OjMYfoNFMgEjk3ZlRh0sPY1zUOK+ew18YlsWUhx+FIjwCu/79Ef73l+dx22/+6NxGY1h4RwFLgGBZMSoq9vi7Gn6VFGbD/jNHkBodgF16DAsGDAAGYJhrP7MtP7f3nOt59objGDDMtefAXHtju/E5tp3zste+tLGuY1r/3FwW26rc68vuCW+iVXVNOH6lChznXP17WnLvyOPTPFtogHqAx2UxDAudbjbKK3ZAHpqMkJA+PNSwrTJLGYSMEGqp2ivlB4qRs+dCrgnH5n+8je/efcPf1emxKGAJEGFhPfMbiDvCAeRUlkKj0QfUB6tzmBd3bWG55p+5az87rvu5vecdzgZi188ccG2BuubtzWVznP3a844bznfdc3BcK4u7Vtb15bb/XMu+wbUw3vVsDg7nDTVostkRKhFhSEQo2Gt/IxW9pCcxBMAJw2mo7YN5K5NlRCi++gWiIn+G0NAE3soFnH/fR41HgypBnCeS0m+BTKXCxteXw9rYAEPeRXAOBxiWRl7whQIWElBGx2mQdbkKo+M0/q6KS+sWEOJLOSVmXK2uh4BlMHqgBqG9PMGgoh68Ds7nOA4azS3wxoCLQyWHkB7V/jpzPVVs6hDMX/Em/v3s7wAADocdAgpYeNO7734ScMJCxagqoPWFerPy2kacLKoGxwFJkQpkpPSOLp+ukIvkqGmqgUKs4KW8lm5DfhktRogFYqgkKt7LDnQR/frj0b9/BJE0BAJhzx5T5WsUsJCAMzRWjRNXqjE0Vu3vqhAfabTZkVVQhQarHeFyCaYm6QKqWzBQDNEOwRHDEYyPHu/vqnSI4zgcMx7rNV1BN2IYBipdpL+r0SNRwEICjl4pxYkr1f6uBvEyjuNw5qoZBnMDxEIWo+M0lO34JkQCEWwOm7+r0amDJQd7XVcQ8Q0KWEhASo5UIqfEjJSoAJwxRDxiMDfgdLEJADAoWoXBfXpft4EnGDBwcA6wATimylBnQIgwpFd2BRHvC7y/eEIA9A2X4Uqlxd/VIDxpsNqx53wZMnMMKKtpxLRkHTJS9IhUSf1dtaCTrElGbmWuv6vRBsdxOF52HMN1w/1dFdJDUQsLCVjxEaG4VFbbY7KV9jYcx+FEkQkVtY2QigQYG6+BREhdPp6KkEUgpzLH39Vo4+DVgwE9toYEPwpYSMBK0Cmw9UwpBSxBpri6HrklZjAMMKSPGsNo8HSPV1pXCplIBqWYunCJ91DAQgJan7AQFFVZEBMm83dVSCcsTTYcKaiCze5AtDqEpiJ7WZgkDJUNldBI/Z+viOM4ZJdl99pZQcR3KGAhAW1QtApbz5RSwBKAHA4Ox69Uo9rShBCxAOMHhNNq2z6SGp6KgyUHcUufW/xdFRy4eoC6gohPUMBCAp5WIYGxpgE6BQ3QDASFFRZcMNaAYYBhsWHQhHp38TzSloAVwBEASy2U1JYgVBRKXUHEJyhgIQFveKwa284aMGMQJWPyl5oGK7IuV8Hh4NBXI6MunwAgYASwOWwQsv55G+c4DifKT1BXEPEZClhIwGMYBqoQEaotTVDLxP6uTq9hd3A4VlgFc70VcokQExO0EFKXT8AYrB2M0+WnMUw3zC/n3391PyZET/DLuUnvRAELCQpj+muolcVH8spqkV9eB5ZlMCI2DCoZrYcSiFQSFcxNZr+c+2rtVSjECt7WNCKkKyhgIUGBYRjIxELUNdp6/Yq93mCyWHG0sBIcB/TXhlKXD+kQx3E4WX6SuoKIz9E7Pwka6QPCseuckT5MeWKzO5B1uQqWJhsUUhEmJ+ogYGnBwWCil+lRWleKyFDftTzuK96HW6L9PzuJ9D4UsJCgIWAZCFgGDVY7LZLngQuGGhRWWiBgGYzsFwaFlLp8glViWCL2Fu/1WcBSXFsMlUQFuZiSORLfo4CFBJXxA7TYf7EcU5N1/q5KUKmsa0L2lSoAQEKEglqpegiG8V2LmINz4HT5acyMm+mzcxJyPQpYSFARC1k4OA42u4NmrNyE1e7AkfxK1FvtUMvEmJKoA0tdPj2OWCBGo70REoHEq+fZV7wvIBLVkd6LAhYSdMYP0OLApQpMSozwd1UCUk6JGSWmeghYFqPjwiAT023ek6Vp03Cy7CRGR4722jmKaooQJglDqCjUa+cg5GbonYwEnRCxAI02BxwOjloMrimracTJomowDJAUqURKFGUe7S1kIhnqbfVeK9/BOXCm4gx1BRG/o4CFBKWx8Rocyq/A+AFaf1fFbxptdhzJr0KjzQ6tXIJpyTqfjmkgvcO+4n2Y2Geiv6tBCAUsJDgppSLUNtjAcVyv+pDmOA6ni80w1jRALGQxOk5DM6YI+in7ocBUgDhVHK/lXqm5Ao1UA5mIFh8l/kejFknQGtkvDEcvV/m7Gj5RampAZo4BO88ZoVNKkJGix8SBERSsEADOgKWwppDXMh2cA2crzmKwdjCv5RLSXdTCQoJWuFzSowOWBqsdP+VXwmp3QK+UUpcP8am9RXupK4gEFApYSFAbEqPCyaJqpMWo/V0VXnAchxNFJlTUNkIqEmBsvAYSIbWikJsLEYagzlrHy0yeK+Yr0IZoqSuIBBTqEiJBLUoVglJTg7+r4bGiKgsycwzYkWtEH3UIMlL0mJCgpWCFdNnQiKE4WXbS43LsDjvOVp7FIO0gHmpFCH+ohYUEvaRIBXJLzUiODK6pvJYmG44UVMFmdyD6WpBCSHeJBWJYHVaPy6FZQSRQUcBCgl6/8FBsPVMaFAGLw8Hh+JVqVFuaECIWYPyAcIgoYy/hkScz5wrNhdDKqCuIBCYKWEiP0F8bivzyOvTXBmYmzssVdbhorAXLMBgWq0ZYaJi/q0R6oMSwRJyvOo8kTZLbx9odduRW5mJG3Awv1IwQz7n11W7VqlVIS0uDUqmEUqlEeno6Nm/e7NrOcRxefvllREdHIyQkBFOmTMGZM2duWu6GDRuQmpoKiUSC1NRUbNy40f1XQnq1gXoFLhhq/F2NVmoarNh5zojMHAOsdgcyUvSYmqxDWKjY31UjPVRkaCQMFkO3jt1bvBcTY6griAQutwKWmJgYvP7668jKykJWVhamTZuGuXPnuoKSN998E++88w7+8Y9/4MiRI4iMjMT06dNRU9PxB8nBgwcxb948LFy4ECdOnMDChQtx//334/Dhw569MtLrRKtDUFztvRTlXWF3cDhSUIkduQacvWrGxAQtMlL0SNAp/FovQjpz2XwZOpkOIcIQf1eFkA4xHMdxnhSg0Wjw1ltv4ZFHHkF0dDSefPJJPPvsswCAxsZG6PV6vPHGG/jlL3/Z7vHz5s2D2Wxu1VIza9YshIWF4YsvvuhyPcxmM1QqFUwmE5TKwB/LQLxj65lSzBgU6fPzXiqrRUF5HViWwYi+YVCFiHxeB0IAINuYjThlHNRSdZf2tzvsyCzMpK4g4jdd/fzu9mg/u92OdevWoa6uDunp6cjPz0dpaSlmzGj5o5dIJJg8eTIOHDjQYTkHDx5sdQwAzJw5s9NjCOlIuFyCsppGn5zLZLFiZ66zy4dlGGeXT5KOghXiV4O1g3Gm4uZd8c32FO3BpJhJXqwRIfxwe9DtqVOnkJ6ejoaGBsjlcmzcuBGpqamuAEOvbz01U6/X4/Llyx2WV1pa2u4xpaWlndajsbERjY0tH0xms9ndl0J6oBF91dh21uC1Vhab3YGsy1Woa7RBFSLC5MQIWjGaBBQhK4Sds3dp3wJTASJDIyEVSr1cK0I853bAkpSUhOzsbFRXV2PDhg1YtGgRdu/e7dp+43S6rkyx684xK1euxPLly92sPenpGIaBMkQEk8UKlYy/lo7zhhpcqbRAwDIYFaeBXEIT7EjgYhkWdocdArbjxIM2hw0Xqi9ger/pPqwZId3ndpeQWCxGQkICRo0ahZUrV2Lo0KF47733EBnp/EZ7Y8uI0Whs04JyvcjISLePAYClS5fCZDK5HleuXHH3pZAeakycBj8VVHpcTmVdE3bkGrAj14AQkQAZKXpMSdJRsEIC3qDwQTftFtpbtJe6gkhQ8ThjFcdxaGxsRP/+/REZGYlt27a5tjU1NWH37t0YP358h8enp6e3OgYAtm7d2ukxgHN8TPP06uYHIQDAsgykIhaWJpvbxzbZHDhwsRw7cg0oqKjDlEQdpiXrEauhRFokeIRJw1DdWN3h9jxTHqLl0ZAIJL6rFCEecuur4rJly3DbbbchNjYWNTU1WLduHXbt2oUtW7aAYRg8+eSTeO211zBw4EAMHDgQr732GmQyGRYsWOAq4+GHH0afPn2wcuVKAMDvf/97TJo0CW+88Qbmzp2Lb775Btu3b8e+ffv4faWkV0mPD8fu82VdSnfPcRxySmpQYqqHSMBiVFwYZGJqRSE9k81hw6XqS9QVRIKOW+/KBoMBCxcuRElJCVQqFdLS0rBlyxZMn+78w//Tn/6E+vp6/PrXv0ZVVRXGjh2LrVu3QqFoyUFRWFgIlm1p2Bk/fjzWrVuH559/Hi+88AIGDBiA9evXY+zYsTy9RNIbCQUsWJZBo83e4QKCxpoGnCoygWGA5EglUqOplY70HBEhETBajNDJdK2ep1lBJFh5nIclUFAeFnKjRpsdBy5VYGpSyxt2g9WOrIIqNNntCA+VIC1G1e11VwgJZBzHORcyvC57bV51HqwOa7dS9xPiLV39/KZ2b9JjSYQCOBwcbHYHckpqUFbbAJGAxeg4DaSijmdPENITMAwDDi3fR60OK/JMebi1361+rBUh3UcBC+nR0geE4/tTJRgXH44hMSp/V4cQnxKyQljtVogEIuoKIkGPAhbSo8nEQswd1sff1SDEL9K0aThZfhJqiRqxiliIBbTwJgleHk9rJoQQEpjkYjlMjSbkm/KRGJbo7+oQ4hFqYSGEkB5MLpJjmG6Yv6tBiMcoYCGEkB5sTNQYf1eBEF5QlxAhhBBCAh4FLIQQQggJeBSwEEIIISTgUcBCCCGEkIBHAQshhBBCAh4FLIQQQggJeBSwEEIIISTgUcBCCCGEkIBHAQshhBBCAh4FLIQQQggJeBSwEEIIISTgUcBCCCGEkIBHAQshhBBCAh4FLIQQQggJeEJ/V4AvHMcBAMxms59rQgghhJCuav7cbv4c70iPCVhqamoAALGxsX6uCSGEEELcVVNTA5VK1eF2hrtZSBMkHA4Hrl69CoVCAYZh/F0dvzCbzYiNjcWVK1egVCr9XR1yHbo2gYuuTeCiaxO4+Lw2HMehpqYG0dHRYNmOR6r0mBYWlmURExPj72oEBKVSSTd3gKJrE7jo2gQuujaBi69r01nLSjMadEsIIYSQgEcBCyGEEEICHgUsPYhEIsFLL70EiUTi76qQG9C1CVx0bQIXXZvA5Y9r02MG3RJCCCGk56IWFkIIIYQEPApYCCGEEBLwKGAhhBBCSMCjgIUQQgghAY8CliD16quvYvz48ZDJZFCr1e3u8/vf/x4jR46ERCLBsGHD2mwvKCgAwzBtHlu2bPFu5Xs4Pq4NAJw6dQqTJ09GSEgI+vTpgxUrVtx0rQ3Ssa5cl8LCQsyZMwehoaHQarX43e9+h6amJtd2ume8g49rA9A94wvHjh3D9OnToVarER4ejsceewy1tbWt9mnvHvnnP//p8bkpYAlSTU1NuO+++/CrX/2qw304jsMjjzyCefPmdVrW9u3bUVJS4npMmzaN7+r2KnxcG7PZjOnTpyM6OhpHjhzB3//+d7z99tt45513vFXtHu9m18Vut2P27Nmoq6vDvn37sG7dOmzYsAFPPfVUm33pnuEXH9eG7hnvu3r1Km699VYkJCTg8OHD2LJlC86cOYPFixe32ffjjz9udY8sWrTI8wpwJKh9/PHHnEql6nSfl156iRs6dGib5/Pz8zkA3PHjx71St97Ok2vzf//3f5xKpeIaGhpcz61cuZKLjo7mHA4HzzXtXTq6Lj/88APHsixXXFzseu6LL77gJBIJZzKZOI6je8bbPLk2dM9434cffsjpdDrObre7njt+/DgHgLtw4YLrOQDcxo0beT8/tbAQ3HnnndDpdJgwYQL+97//+bs6BMDBgwcxefLkVkmZZs6ciatXr6KgoMB/FevBDh48iMGDByM6Otr13MyZM9HY2IijR4+22pfuGd/qyrWhe8b7GhsbIRaLWy1QGBISAgDYt29fq32feOIJaLVajB49Gv/85z/hcDg8Pj8FLL2YXC7HO++8g//973/44YcfkJGRgXnz5uGzzz7zd9V6vdLSUuj1+lbPNf9eWlrqjyr1eO39n4eFhUEsFrv+z+me8Y+uXBu6Z7xv2rRpKC0txVtvvYWmpiZUVVVh2bJlAICSkhLXfq+88gq+/PJLbN++HfPnz8dTTz2F1157zePzU8ASQF5++eV2Bytd/8jKyuLtfFqtFn/4wx8wZswYjBo1CitWrMCvf/1rvPnmm7ydo6fw9bUBnAPXrsddGzx44/O9Gd/Xpb3/W47jXM/TPdN1vr427e1D90zXdPVaDRo0CJ988gn++te/QiaTITIyEvHx8dDr9RAIBK7ynn/+eaSnp2PYsGF46qmnsGLFCrz11lse11PocQmEN0888QTmz5/f6T5xcXFercO4cePw0UcfefUcwcjX1yYyMrLNt0Kj0QgAbb5F9mZ8XpfIyEgcPny41XNVVVWwWq2d/p/TPdM+X18bume6z51rtWDBAixYsAAGgwGhoaFgGAbvvPMO+vfv3+Gx48aNg9lshsFg8OhaUMASQLRaLbRarV/rcPz4cURFRfm1DoHI19cmPT0dy5YtQ1NTE8RiMQBg69atiI6O9nrQGkz4vC7p6el49dVXUVJS4roHtm7dColEgpEjR3Z4HN0z7fP1taF7pvu6c62aA481a9ZAKpVi+vTpHe57/PhxSKXSDqesdxUFLEGqsLAQlZWVKCwshN1uR3Z2NgAgISEBcrkcAHDx4kXU1taitLQU9fX1rn1SU1MhFovxySefQCQSYfjw4WBZFps2bcL777+PN954w0+vqmfg49osWLAAy5cvx+LFi7Fs2TJcuHABr732Gl588UVq3u6mm12XGTNmIDU1FQsXLsRbb72FyspKPP300/jFL34BpVIJAHTPeAkf14buGd/4xz/+gfHjx0Mul2Pbtm145pln8Prrr7uCkU2bNqG0tBTp6ekICQnBzp078dxzz+Gxxx7zfGVn3ucdEZ9YtGgRB6DNY+fOna59Jk+e3O4++fn5HMdx3Nq1a7mUlBROJpNxCoWCGzlyJPfvf//bPy+oB+Hj2nAcx508eZKbOHEiJ5FIuMjISO7ll1+m6Zke6Mp1uXz5Mjd79mwuJCSE02g03BNPPNFqmizdM97Bx7XhOLpnfGHhwoWcRqPhxGIxl5aWxn366aettm/evJkbNmwYJ5fLOZlMxg0ePJh79913OavV6vG5GY6jNICEEEIICWw0S4gQQgghAY8CFkIIIYQEPApYCCGEEBLwKGAhhBBCSMCjgIUQQgghAY8CFkIIIYQEPApYCCGEEBLwKGAhhBBCSMCjgIUQQgghAY8CFkIIIYQEPApYCCGEEBLwKGAhhBBCSMD7/wFs5MB3L0SKAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing w/option 1 - set the cluster area thresholds to unitize cluster use\n",
    "#NOTE -- THIS MAY NOT BE RIGHT -- DEPENDS ON HOW WE GENERATED THE HDpoly's\n",
    "\n",
    "CCBuse, CCBareaFrac, CCBarea = [0. for CCB in CCBlist], [0.5 for CCB in CCBlist], [geo.area for geo in CCBgeom]\n",
    "for j,geo in enumerate(CCBgeom):\n",
    "    nIntersections = 0\n",
    "    print(\"working on cluster no\",j,\"containing counties\",CCBlist[j] )\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    HDfrac = [ 0. for t in range(nHDs) ]\n",
    "    for t in range(nHDs):\n",
    "        if HDcountyNo[t] in CCBlist[j]:\n",
    "            HDfrac[t] = 1.\n",
    "        else:\n",
    "            HDfrac[t] = HDpoly[t].intersection(geo).area / CCBarea[j]\n",
    "    idx = np.argsort(HDfrac)\n",
    "    i = nHDs\n",
    "    minFrac, stillGoing = 1.0, True\n",
    "    while CCBuse[j] < 1.000 - 0.5 * nDistricts*np.average(HDweight) and i > 0 and stillGoing:\n",
    "        i -=1\n",
    "        nIntersections +=1\n",
    "        t = idx[i]\n",
    "        currFrac = HDfrac[t]\n",
    "        if currFrac > 0:  #protects against clusters with < 1 district's worth of nonzero intersection\n",
    "            minFrac = currFrac\n",
    "        else:\n",
    "            stillGoing = False\n",
    "            break\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        if CCBuse[j] > 0.5 and CCBuse[j] - HDweight[t] * nDistricts < 0.5:\n",
    "            print(\"halfway there! last use was\",r5(HDfrac[t]))\n",
    "            plotPoly(HDpoly[t],0.2)\n",
    "        #origHDlist[t].append(unitNo)  #postpone this until main loop\n",
    "        #origHDpop[t] += CCBpop[j]     #postpone until main\n",
    "    if not stillGoing:\n",
    "        print(\"WARNING, only\",r5(CCBuse[j]),\" of a district's worth of ensemble intersected the cluster geometry\")\n",
    "        # we could Add more stuff here to inflate the poly and try again ...\n",
    "    CCBareaFrac[j] = currFrac  #HDfrac[t]\n",
    "    print(\"our final fractional capture area to normalize this cluster's usage is\",r5(CCBareaFrac[j]),\"from\",nIntersections,\"intersecting HDs\" )\n",
    "    plotPoly(MAP,0.2)\n",
    "    plotPoly(geo,0.8)\n",
    "    plotCenter(j,geo)\n",
    "    plotPoly(HDpoly[t],1.3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9d8ef17b-820b-4870-b063-897373f57f9a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.013774429140623023, 0.879228852547132, 0.0, 0.48424676611231976]\n",
      "[0.013774429140623023, 0.879228852547132, 0.001, 0.48424676611231976]\n"
     ]
    }
   ],
   "source": [
    "print(CCBareaFrac)\n",
    "CCBareaFrac = [max(0.001,frac) for frac in CCBareaFrac]\n",
    "print(CCBareaFrac)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "aad5e7db-93db-43d8-8196-dd6dd02f3014",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am temporarily overriding these area fractions to test our recovery from incorrect starting pts\n"
     ]
    }
   ],
   "source": [
    "#print(\"I am temporarily overriding these area fractions to test our recovery from incorrect starting pts\")\n",
    "#CCBareaFrac = [0.17, 0.25, 0.1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "217527a2-0acf-43ec-9a25-09e0aecce76d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the main code to determine each HD's pop based on vtd CP's that intersect the HDpoly\n",
      "We'll later add nearby or jettison faraway contiguous units until we approach the aDP\n",
      "  the HD pops and lists already appropriately include captured corner county clusters\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to enforce areaFrac threshold capture for clusters; helps to even up their usage 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on HDno 0\n",
      "working on HDno 300\n",
      "working on HDno 600\n",
      "working on HDno 900\n",
      "working on HDno 1200\n",
      "working on HDno 1500\n",
      "working on HDno 1800\n",
      "working on HDno 2100\n",
      "working on HDno 2400\n",
      "working on HDno 2700\n",
      "working on HDno 3000\n",
      "all done assigning units to HDs based on original HD polygons\n",
      "Here is a scatterplot of active HD pop excess vs relative to target 721714.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, compute the current unit usage, plot its histogram weighted by unit pop\n",
      "unit avg and sd usage are 0.61239 0.17788\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to correcting for discontiguity ...\n",
      "CCB cluster 0 with pop 44650.0 originally had use of 1.055276903999999\n",
      "CCB cluster 1 with pop 65547.0 originally had use of 1.0034878799999993\n",
      "CCB cluster 2 with pop 105949.0 originally had use of 0.9093165280000003\n",
      "CCB cluster 3 with pop 42401.0 originally had use of 0.9776087680000001\n"
     ]
    }
   ],
   "source": [
    "#continuing w/option 1 - now we determine original (nonsmoothed) vtd lists for the original HD polygons\n",
    "print(\"This is the main code to determine each HD's pop based on vtd CP's that intersect the HDpoly\")\n",
    "print(\"We'll later add nearby or jettison faraway contiguous units until we approach the aDP\")\n",
    "print(\"  the HD pops and lists already appropriately include captured corner county clusters\")\n",
    "#see above block for preliminaries\n",
    "nonUnitCounties = list (set([c for c in range(nCounties)]).difference(set(unitCounties)) )\n",
    "areaFrac = [0.5 for u in range(nUnits)]  #default; we will accept unit counties if we capture half their area\n",
    "alter = input(\"enter 1 to enforce areaFrac threshold capture for clusters; helps to even up their usage\")\n",
    "if alter == 1:\n",
    "    for u in range(nUnits):\n",
    "        if allUnits[u] - int(allUnits[u]) == 0.25:  #a county cluster.  Enforce alternate areaFrac's determined above\n",
    "            CCBno = int(allUnits[u] )\n",
    "            areaFrac[u] = CCBareaFrac[CCBno ]\n",
    "            print(\"enforcing areaFrac capture threshold of\",r5(CCBareaFrac[CCBno]),\"for CCBno, uNo\",CCBno,u)\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:  #a county cluster.  Enforce alternate areaFrac's determined above\n",
    "        CCBno = int(allUnits[u] )\n",
    "        areaFrac[u] = CCBareaFrac[CCBno ]\n",
    "        #print(\"enforcing areaFrac capture threshold of\",r5(CCBareaFrac[CCBno]),\"for CCBno, uNo\",CCBno,u)\n",
    "# for c in unitCounties:   #UNCOMMENT TO ENFORCE UNIT COUNTIES TO EQUAL USAGE\n",
    "#    areaFrac[allUnits.index(c+0.5)] = unitCareaFrac[ unitCounties.index(c) ]\n",
    "\n",
    "origHDpop, origHDlist = [0. for t in range(nHDs)], [list() for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HDno\",t)\n",
    "    hC = HDcountyNo[t]\n",
    "    if hC in allFusedCounties:  #using a swelling technique as original HDpoly's look skewy\n",
    "        origHDpop[t], origHDlist[t] = clusterSwell(hdCP[t], CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, aDP)\n",
    "    else:\n",
    "        if hC in unitCounties:\n",
    "            iCP, iClist = countyPop[hC], [allUnits.index(hC+0.5) ] #automatically include the home county if small\n",
    "        else: #must probe in-county list vs HDpoly intersxn\n",
    "            iCP, iClist =  getPolyPop(HDpoly[t], unitCP, unitPop, countyUnitList[hC])\n",
    "        nonCP, nonClist = getNonHCunits(HDpoly[t], hC, allUnits, unitCP, unitPop, allFusedCounties, areaFrac, countyGeom,\n",
    "                                        neighborCountyList, countyUnitList)  #this will miss county clusters; see below\n",
    "        origHDpop[t]  += iCP + nonCP\n",
    "        origHDlist[t] += iClist + nonClist\n",
    "        for j, geo in enumerate(CCBgeom):  #special for corner clusters -- intersection area must clear threshold estbd in a prev block\n",
    "            unitNo = allUnits.index(j+0.25)\n",
    "            if geo.intersection(HDpoly[t]).area >= areaFrac[unitNo] * CCBarea[j]:\n",
    "                origHDpop[t] += unitPop[unitNo]\n",
    "                origHDlist[t].append(unitNo)\n",
    "print(\"all done assigning units to HDs based on original HD polygons\")\n",
    "HDpopExcess = list()\n",
    "for t in popHDlist:\n",
    "    HDpopExcess.append(origHDpop[t] - aDP)\n",
    "print(\"Here is a scatterplot of active HD pop excess vs relative to target\",aDP)\n",
    "plt.scatter(popHDlist, HDpopExcess)\n",
    "plt.axhline(-0.01*aDP,np.min(popHDlist),np.max(popHDlist),ls=\"--\")\n",
    "plt.axhline( 0.01*aDP,np.min(popHDlist),np.max(popHDlist),ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, compute the current unit usage, plot its histogram weighted by unit pop\")\n",
    "origUnitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in origHDlist[t]:\n",
    "        origUnitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(origUnitUse,bins=50,weights=unitPop)\n",
    "origUnitUseAvg, origUnitUseSD = getWeightedAvgAndSD(origUnitUse,unitPop)\n",
    "print(\"unit avg and sd usage are\",r5(origUnitUseAvg), r5(origUnitUseSD) )\n",
    "plt.show()\n",
    "print(\"prior to correcting for discontiguity ...\")\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"with pop\",unitPop[u],\"originally had use of\",origUnitUse[u])\n",
    "\n",
    "HDunitList = [origHDlist[t].copy() for t in range(nHDs) ]  #for safekeeping\n",
    "HDvPop = origHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "48e27209-e726-47d6-a194-784b1c7640cc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "showing woefully underpopped HDs -- usually a discontiguous large pop in original shape not picked up when contig counties enforced\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"showing woefully underpopped HDs -- usually a discontiguous large pop in original shape not picked up when contig counties enforced\")\n",
    "for t in popHDlist:\n",
    "    if origHDpop[t] < 500000 :\n",
    "        plotPoly(HDpoly[t])\n",
    "        plotPoly(countyGeom[HDcountyNo[t]],0.4)\n",
    "        plotPoly(hdCP[t].buffer(0.1),2)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70a8d159-68bb-4436-8a07-0ea73d3f5b94",
   "metadata": {},
   "outputs": [],
   "source": [
    "#END OF OPTION 1 -- SKIP AHEAD TO AFTER OPTION 2\n",
    "###########################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "ecc512e1-cb48-4c0b-90f4-b90458ee23f6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here we compute the map's convex hull.  And here is a dot map of the (shifted) unit centerpoints\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note the MAP convex hull.  Overwrite with your own polygon if desired.\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 - draw polygonal HDs.  ##REQUIRES CONSISTENT TREATMENT OF CCB'S\n",
    "#Can draw for each vtd.  Or, read in tract or blockgroup geometries, use those pops and unit centerpoints\n",
    "print(\"Here we compute the map's convex hull.  And here is a dot map of the (shifted) unit centerpoints\")\n",
    "convexMAP = MAP.centroid\n",
    "for c in range(nCounties):\n",
    "    if c not in allFusedCounties:\n",
    "        convexMAP = convexMAP.union(countyGeom[c])\n",
    "MAPhull = convexMAP.convex_hull.buffer(0.01*convexMAP.area**0.5)\n",
    "plotPoly(MAPhull)\n",
    "for t in popHDlist:\n",
    "    if hdCP[t].disjoint(convexMAP.convex_hull):\n",
    "        plotPoly(hdCP[t].buffer(0.03))\n",
    "        hdCP[t] = nearest_points(convexMAP.convex_hull,hdCP[t])[0]\n",
    "        plotCenter(\"m\",hdCP[t])\n",
    "    else:\n",
    "        plotPoly(hdCP[t].buffer(0.01))\n",
    "plotPoly(convexMAP)\n",
    "plotPoly(convexMAP.convex_hull)\n",
    "plotPoly(MAPhull)\n",
    "for c in allFusedCounties:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "plt.show()\n",
    "\n",
    "print(\"Note the MAP convex hull.  Overwrite with your own polygon if desired.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "17ca412c-cf66-4b4e-aff9-a702d0e3c341",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#option 2, if we are drawing based on VTDs as HD-generators, not tracts\n",
    "nHDs = nTracts\n",
    "popHDlist = list()\n",
    "for t in range(nTracts):\n",
    "    if tractPop[t] > 4:\n",
    "        popHDlist.append(t)\n",
    "HDcountyNo = countyNo.copy()\n",
    "hdCP = tractCP.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "54f09a52-c279-4647-9860-0729d1912b4e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let us establish the (post-squish) point-point distances for all units, about 8 min for 4000-unit state\n",
      "working on unit-unit distances for unit 0 out of 3108 . Time = 0\n",
      "working on unit-unit distances for unit 200 out of 3108 . Time = 35\n",
      "working on unit-unit distances for unit 400 out of 3108 . Time = 68\n",
      "working on unit-unit distances for unit 600 out of 3108 . Time = 97\n",
      "working on unit-unit distances for unit 800 out of 3108 . Time = 124\n",
      "working on unit-unit distances for unit 1000 out of 3108 . Time = 148\n",
      "working on unit-unit distances for unit 1200 out of 3108 . Time = 171\n",
      "working on unit-unit distances for unit 1400 out of 3108 . Time = 191\n",
      "working on unit-unit distances for unit 1600 out of 3108 . Time = 209\n",
      "working on unit-unit distances for unit 1800 out of 3108 . Time = 225\n",
      "working on unit-unit distances for unit 2000 out of 3108 . Time = 238\n",
      "working on unit-unit distances for unit 2200 out of 3108 . Time = 249\n",
      "working on unit-unit distances for unit 2400 out of 3108 . Time = 257\n",
      "working on unit-unit distances for unit 2600 out of 3108 . Time = 263\n",
      "working on unit-unit distances for unit 2800 out of 3108 . Time = 268\n",
      "working on unit-unit distances for unit 3000 out of 3108 . Time = 271\n",
      "All done; total elapsed  271 seconds for CO with 8 districts to map\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 ....... ##########  THIS IS FOR TRACT - TRACT; SEE LATER FOR unit - unit ...\n",
    "print(\"Let us establish the (post-squish) point-point distances for all units, about 8 min for 4000-unit state\")\n",
    "#NOTE: FOR LARGE STATES, RESTRICT THE SEARCH TO COUNTIES WITHIN A 3/SQRT(nDistrict) DIAMETER OF THE HOME UNIT\n",
    "#    NEED TO TEST THIS ON A LARGE STATE **************\n",
    "uuDist = [[int(maxD+1) for t in range(nHDs)] for t in range(nHDs)] #default = too big to capture\n",
    "closeCountyList = [list() for c in range(nCounties)]\n",
    "closeCountyDist = maxD   #min(maxD,3./float(nDistricts)**0.5 * maxD )  #use above maxD for these counties as well\n",
    "xScaleSquared = xScale*xScale\n",
    "if closeCountyDist >= maxD:  #small state\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]  #all counties are close enough\n",
    "else:\n",
    "    for c in range(nCounties):\n",
    "        closeCountyList[c].append(c)\n",
    "        for cc in range(c+1,nCounties):\n",
    "            if cc in neighborCountyList[c]:\n",
    "                closeCountyList[c].append(cc)\n",
    "                closeCountyList[cc].append(c)\n",
    "            else:    \n",
    "                dist = getLongDist(countyCP[c], countyCP[cc],xScale)\n",
    "                if dist < closeCountyDist:\n",
    "                    closeCountyList[c].append(cc)\n",
    "                    closeCountyList[cc].append(c)\n",
    "startTime = time.time()\n",
    "populatedTractList = popHDlist.copy()  #nomenclature\n",
    "for t in populatedTractList:\n",
    "    if t %200 == 0:\n",
    "        print(\"working on unit-unit distances for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime))\n",
    "    uuDist[t][t] == 0.\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "                dist = getLongDist(hdCP[t], hdCP[tt],xScale)\n",
    "                uuDist[t][tt], uuDist[tt][t] = dist, dist\n",
    "print(\"All done; total elapsed \",int(time.time()-startTime),\"seconds for\",STATE,\"with\",nDistricts,\"districts to map\" )\n",
    "plt.hist(uuDist)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bc91a02a-52b2-4ac3-afc2-7f1650e32922",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similar to above, but for angles\n",
      "working on unit-unit angles for unit 0 out of 3108 . Time = 0\n",
      "working on unit-unit angles for unit 200 out of 3108 . Time = 18\n",
      "working on unit-unit angles for unit 400 out of 3108 . Time = 35\n",
      "working on unit-unit angles for unit 600 out of 3108 . Time = 50\n",
      "working on unit-unit angles for unit 800 out of 3108 . Time = 64\n",
      "working on unit-unit angles for unit 1000 out of 3108 . Time = 76\n",
      "working on unit-unit angles for unit 1200 out of 3108 . Time = 87\n",
      "working on unit-unit angles for unit 1400 out of 3108 . Time = 98\n",
      "working on unit-unit angles for unit 1600 out of 3108 . Time = 107\n",
      "working on unit-unit angles for unit 1800 out of 3108 . Time = 115\n",
      "working on unit-unit angles for unit 2000 out of 3108 . Time = 122\n",
      "working on unit-unit angles for unit 2200 out of 3108 . Time = 128\n",
      "working on unit-unit angles for unit 2400 out of 3108 . Time = 132\n",
      "working on unit-unit angles for unit 2600 out of 3108 . Time = 135\n",
      "working on unit-unit angles for unit 2800 out of 3108 . Time = 138\n",
      "working on unit-unit angles for unit 3000 out of 3108 . Time = 139\n",
      "All done with angles; total elapsed seconds = 139\n"
     ]
    },
    {
     "data": {
      "image/png": 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f3QoxlmVp2bJleu2113Tw4EElJyeHPJ6cnCyfz6eysjL7vpaWFpWXlyszM1OSlJaWpsGDB4fU1NTU6PTp03ZNRkaG/H6/jh8/btccO3ZMfr/frgEAAANbt85OWrp0qfbs2aPXX39d0dHR9oiL1+vV0KFD5fF4lJ+fr8LCQo0dO1Zjx45VYWGhhg0bpnnz5tm1CxYs0KpVqzRy5EjFxsZq9erVSk1Ntc9WGj9+vGbMmKGFCxdq69atkqRFixYpJyeHM5MAAICkboaYLVu2SJKmTJkScv9LL72kp556SpL09NNPq7m5WUuWLFF9fb3S09N14MABRUdH2/UbN25URESE5syZo+bmZk2dOlU7duzQoEGD7Jrdu3drxYoV9llMubm5Ki4u7sk6AgCAMNStEGNZVqc1Ho9HBQUFKigoaLdmyJAh2rx5szZv3txuTWxsrHbt2tWd9gAALpe6M1VP6kmn20CY4LuTgK4o8DrdAQDgNoQYAABgJEIMAAAwEiEGAAAYiRADoF2X1rzvdAsA0C5CDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWKAbvj6mjecbgEwju9QldMtIEwRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAGAkQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEjdDjHvvfeeZs6cqcTERHk8Hu3bty/k8aeeekoejydkmTRpUkhNMBjU8uXLNWrUKA0fPly5ubm6dOlSSE19fb3y8vLk9Xrl9XqVl5enhoaGbq8gAAAIT90OMU1NTZowYYKKi4vbrZkxY4Zqamrs5c033wx5PD8/X3v37lVJSYkOHz6sxsZG5eTkqLW11a6ZN2+eqqqqVFpaqtLSUlVVVSkvL6+77QIAgDAV0d0nZGdnKzs7u8OaqKgo+Xy+Oz7m9/v14osv6pVXXtG0adMkSbt27VJSUpLeeecdPfHEEzp79qxKS0tVUVGh9PR0SdL27duVkZGhc+fOady4cd1tGwAAhJk+mRPz7rvvKi4uTvfdd58WLlyouro6+7HKykpdv35dWVlZ9n2JiYlKSUnRkSNHJElHjx6V1+u1A4wkTZo0SV6v1665XTAYVCAQCFkAAED46vUQk52drd27d+vgwYNav369Tpw4occff1zBYFCSVFtbq8jISI0YMSLkefHx8aqtrbVr4uLi2rx2XFycXXO7oqIie/6M1+tVUlJSL68ZAABwk24fTurM3Llz7X+npKRo4sSJGjNmjN544w3Nnj273edZliWPx2PfvvXf7dXcau3atVq5cqV9OxAIEGQAAAhjfX6KdUJCgsaMGaPz589Lknw+n1paWlRfXx9SV1dXp/j4eLvm8uXLbV7rypUrds3toqKiFBMTE7IAAIDw1ech5urVq6qurlZCQoIkKS0tTYMHD1ZZWZldU1NTo9OnTyszM1OSlJGRIb/fr+PHj9s1x44dk9/vt2sAAMDA1u3DSY2Njfr444/t2xcuXFBVVZViY2MVGxurgoICPfnkk0pISNAf/vAHPfPMMxo1apR++MMfSpK8Xq8WLFigVatWaeTIkYqNjdXq1auVmppqn600fvx4zZgxQwsXLtTWrVslSYsWLVJOTg5nJgEAAEk9CDEnT57UY489Zt++OQ9l/vz52rJli06dOqWXX35ZDQ0NSkhI0GOPPaZXX31V0dHR9nM2btyoiIgIzZkzR83NzZo6dap27NihQYMG2TW7d+/WihUr7LOYcnNzO7w2DQAAGFi6HWKmTJkiy7Laffztt9/u9DWGDBmizZs3a/Pmze3WxMbGateuXd1tDwAADBB8dxIAADASIcYlvr7mDadbAADAKIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBgAAHrgV4sPOt3CgEeIAQAARiLEAAAAIxFiAACAkQgxAIAB6ey3xjvdAu4SIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAMEjqzlSnW3ANQgwAADASIQYAABiJEAMAAIxEiAEAAEYixAAAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwAAjESIAQAARiLEAAAAIxFiAAD9r8DrdAcIA4QYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBIhBggTF1a877TLQBAnyLEAAAAIxFiAACAkQgxAADASN0OMe+9955mzpypxMREeTwe7du3L+Rxy7JUUFCgxMREDR06VFOmTNGZM2dCaoLBoJYvX65Ro0Zp+PDhys3N1aVLl0Jq6uvrlZeXJ6/XK6/Xq7y8PDU0NHR7BQEAQHjqdohpamrShAkTVFxcfMfHn3/+eW3YsEHFxcU6ceKEfD6fpk+frmvXrtk1+fn52rt3r0pKSnT48GE1NjYqJydHra2tds28efNUVVWl0tJSlZaWqqqqSnl5eT1YRQAAEI4iuvuE7OxsZWdn3/Exy7K0adMmrVu3TrNnz5Yk7dy5U/Hx8dqzZ49++tOfyu/368UXX9Qrr7yiadOmSZJ27dqlpKQkvfPOO3riiSd09uxZlZaWqqKiQunp6ZKk7du3KyMjQ+fOndO4ceN6ur4AACBM9OqcmAsXLqi2tlZZWVn2fVFRUZo8ebKOHDkiSaqsrNT169dDahITE5WSkmLXHD16VF6v1w4wkjRp0iR5vV675nbBYFCBQCBkAfrC+rk5TrcAAFAvh5ja2lpJUnx8fMj98fHx9mO1tbWKjIzUiBEjOqyJi4tr8/pxcXF2ze2Kiors+TNer1dJSUl3vT4AAMC9+uTsJI/HE3Lbsqw2993u9po71Xf0OmvXrpXf77eX6urqHnQOAABM0ashxufzSVKb0ZK6ujp7dMbn86mlpUX19fUd1ly+fLnN61+5cqXNKM9NUVFRiomJCVkAAED46tUQk5ycLJ/Pp7KyMvu+lpYWlZeXKzMzU5KUlpamwYMHh9TU1NTo9OnTdk1GRob8fr+OHz9u1xw7dkx+v9+uAQAAA1u3z05qbGzUxx9/bN++cOGCqqqqFBsbq3vvvVf5+fkqLCzU2LFjNXbsWBUWFmrYsGGaN2+eJMnr9WrBggVatWqVRo4cqdjYWK1evVqpqan22Urjx4/XjBkztHDhQm3dulWStGjRIuXk5HBmEgAAkNSDEHPy5Ek99thj9u2VK1dKkubPn68dO3bo6aefVnNzs5YsWaL6+nqlp6frwIEDio6Otp+zceNGRUREaM6cOWpubtbUqVO1Y8cODRo0yK7ZvXu3VqxYYZ/FlJub2+61aQAAwMDT7RAzZcoUWZbV7uMej0cFBQUqKChot2bIkCHavHmzNm/e3G5NbGysdu3a1d32AADAAMF3JwEAACMRYgAAgJEIMQAAwEiEGAAAYCRCDAAAMBIhBgAAGIkQAwBAH0vdmep0C2GJEAMAAIxEiAEkXVrzvtMtAAC6iRADAHAEHx5wtwgxAADHfH3NG063AIMRYgDAYEwYxUBGiAEAAEYixAAAACMRYgAAgJEIMfirAq/THQAA0GWEGAAAYCRCDAAAMBIhBgAAA5z91ninW3AdQgwAADASIQb4C64cCgBmIcQAgAH4nqG/+u3BbzjdAlyCEAMAAIxEiAGAPsLoCSRGjvoSIQYwFRcnBDDAEWIAAL2Cb9RGfyPEAACMwbVScCtCDACg1zEfCP2BEAMAAIxEiAEAAEYixACG8x2qcroFgNOI4QhCDAA4jPkj5uHDgzsQYgAAgJEIMQCAXlNQUOB0CxhACDH9gG9HBgCg9xFiAAC9qwdficEcE/QEIQYA3I7vyUIfMX1SOSEGAIAeMvnU8nD4ritCDAB0Ed/bg4HEhEnahBgAjiEUALgbhBgAYY+wBDfoj5GNgfa7TogB+pipO5VwOF4OILwRYoB2mDxhb6Az/YwLAF1DiAEcsH5ujtMtOIaLPwLoLYQYGIvDHUD4MuHMGDiv10NMQUGBPB5PyOLz+ezHLctSQUGBEhMTNXToUE2ZMkVnzpwJeY1gMKjly5dr1KhRGj58uHJzc3Xp0qXebhUYEAbyqA/Mx6FBdKRPRmK+/e1vq6amxl5OnTplP/b8889rw4YNKi4u1okTJ+Tz+TR9+nRdu3bNrsnPz9fevXtVUlKiw4cPq7GxUTk5OWptbe2LduEgDi30DDv2/vWrxQedbmFAYZQVXdUnISYiIkI+n89e7rnnHklfjsJs2rRJ69at0+zZs5WSkqKdO3fqz3/+s/bs2SNJ8vv9evHFF7V+/XpNmzZNDz74oHbt2qVTp07pnXfe6Yt2jcEb/pdMPdsH7sbvFWCePgkx58+fV2JiopKTk/WjH/1In3zyiSTpwoULqq2tVVZWll0bFRWlyZMn68iRI5KkyspKXb9+PaQmMTFRKSkpdg0AYADgO6Ncwc0jv70eYtLT0/Xyyy/r7bff1vbt21VbW6vMzExdvXpVtbW1kqT4+PiQ58THx9uP1dbWKjIyUiNGjGi35k6CwaACgUDIEg6Y3AYAwJ31eojJzs7Wk08+qdTUVE2bNk1vvPHlIZCdO3faNR6PJ+Q5lmW1ue92ndUUFRXJ6/XaS1JS0l2sBXqT71CV0y0AAMJQn59iPXz4cKWmpur8+fP2WUq3j6jU1dXZozM+n08tLS2qr69vt+ZO1q5dK7/fby/V1dW9vCYA7la4nCnFxFPAHfo8xASDQZ09e1YJCQlKTk6Wz+dTWVmZ/XhLS4vKy8uVmZkpSUpLS9PgwYNDampqanT69Gm75k6ioqIUExMTsiB8cZgNABDR2y+4evVqzZw5U/fee6/q6ur07LPPKhAIaP78+fJ4PMrPz1dhYaHGjh2rsWPHqrCwUMOGDdO8efMkSV6vVwsWLNCqVas0cuRIxcbGavXq1fbhKQAAelPqzlSdmn+q80K4Tq+HmEuXLulv//Zv9cc//lH33HOPJk2apIqKCo0ZM0aS9PTTT6u5uVlLlixRfX290tPTdeDAAUVHR9uvsXHjRkVERGjOnDlqbm7W1KlTtWPHDg0aNKi32wUAuNzX17yhPzz3fafbgAv1eogpKSnp8HGPx6OCgoIODwcMGTJEmzdv1ubNm3u5OwCA26yfmyMtftbpNmAgvjsJAAzBBS+BUIQYoANcxRUIb5wkYDZCDGCwcDll2QRc7whwH0IMcAd84R8AuB8hBgAAGIkQA6P1yheThfGXzDERFEA4I8QAaOO3B7/hdAsA+kg4nbBAiAEA4C+YLG8WQgyc4cAhHHZOAxNnFQHhixADDAC8kYc3rnWCgYoQgwGNnT8AmIsQM4BxLRSEO37HgbuTujPV6RY6RIhBvwin2fA95fadAQCYhhBjGD5ZAgDwJUIM0InenDfTKxfnA3oqjC/saCom3d8dQgzQD5hADLgfV7g2DyHGxW6dQxGOn+DDcZ3CXbgfzgyHKxXf+kY8kOaiEUAGJkIMMECEewABMPAQYgAAA97djAwPpBEvtyHEAP2NyZX9IlwOLzCfCu0q8A74r1MhxADALbieD2AOQgx6xKRPuUwghqkIVEDHCDG9iImTbQ30oc67sX5ujrHXkDC177vR33//beZhcJjSNUz6kGc6Qgx6FcfvQZhHX7k9HPf3/qY7o7p8gOsfhBgArtbbZ37c7Rtff1xLhrNdgK4hxKD3MayNAcSJT9w3RyTC4eJ86B0DdQSUENNLTJ0DwE4wfLjt/7Kz0YTO+jVip/yXwN6bcyBM3Zc4qa8n77vxMDknLHyJEAPAUW54g+iL4MCZRUDfI8S4lNs+VQP9hQmRALqKEIMBgVMe715/bsObP6vPwnwn87YurXnf8bldvbnu7Y0KcegKpiPEOI1JsICjjJh700XdmScRTuuNgYsQAwBhLFwPTdujS3wQHNAjaoSYXsAxfHN2lL5DVXwChWuxL0FfCOffK0IMcItw/mO/G2wXoPf19d/VQDgNmxDjIDecWno3TP5uH5MwcoTeYPr+BrgTQgwAADASIcYFBsKQH/qX2y+0Fs6jS2e/Nd71ox63ny7/24PfcP3vjBNC5voxgdiVCDHoNkIXwkVvX/vGLYdX7yok9uDNOpxDqfHCPHwRYtDv3P4pFbcJ853gQMc3Zt9Zj4KZS/5WOtrH3hxdCpf9MCEG/aa/TsM25XTvcBDuhyA6OnuEEUnc6mYo4PeifxFiXKg7n4zC/U0E3Rcun7AwMLn9Q8jX17zBJQdchBBjoJvH3ft7WJA3R/SlXvsE65IhfRPxN9677jhHqp9+P3v7A65bv3+OENPL2gsWtyb3js4E6PHEwLv4w+irY+Ju/aUH0DGnRhqYn9O3ujLPx7RJ2oSYfuSWMxf6SleSf08/HXS47Qz95N2bIc+JHU+ffGo39P8Sd8YHmfa5adu4qZfuIsQY6m4+sXA8d+By+3wDAM64/X2hs/cYt+xLCDF9rFeO8/fip1OTE7fknj8cdE1BQUGfjtChfeE+8ou+Y9J+1vUh5oUXXlBycrKGDBmitLQ0vf++e05f6zSguHhovKs7uF8tPmjUL3Q4Y74AEB6cOA27t0Kt71CVq+bNuDrEvPrqq8rPz9e6dev0wQcf6Hvf+56ys7N18eJFp1sbuO4QzPrrF9pNk9J6+1PuzYDS3ohEV4NkfwWdNj+nk8DOtTPcg8PJ6Ck3/u64OsRs2LBBCxYs0E9+8hONHz9emzZtUlJSkrZs2eJ0a/ZOu7uHZ9z6aTocT63sylUrTROO/09uZ/oh2HDRlTdQN40QOMHU/drdiHC6gfa0tLSosrJSa9asCbk/KytLR44caVMfDAYVDAbt236/X5IUCAT6psGgpWvBJt3Qn/X59eu60dSo5pYmNTXdUGtzq4LBoAJqW9PY2tpuTXPLDd1oiuxxjbqwrjeCbfttbL3za9xaEwgE2l2nu13vrvwf3anf1uZWXQs2KeD5a99t+g0E2u33xNj7FPz/nuxwnW7dNrfXdLXvO/X7+fXruhH8ct3fLZ+ghNbBWrt2rVrHtNqv224vf1kn+3U62DZ3Wqeu9H3z/+r2fptbvnz+rT8nEAhIQUubZz+hrWN+ohUtQ+zf0ZD1DgRCXqe9/8v2arrSd0d/L4FAoM3fy82fc/vf1J166U7N7evdmZDt04W/l7vZl3S0TrfWdGff2ZV9QCAQuKv9RFf3oV3pe1t+uRZtmtzu30vcbw7r6W7s+zraT/y/H/9a9/2w823TFbf+Hnd1H9Cd/UQgEOj1fUlP3Hxdy7I6L7Zc6tNPP7UkWb/73e9C7v/Xf/1X67777mtT/4tf/MKSxMLCwsLCwhIGS3V1dadZwbUjMTd5PJ6Q25ZltblPktauXauVK1fat2/cuKE//elPGjly5B3ruyoQCCgpKUnV1dWKiYnp8euEM7ZR17CdOsc26hzbqHNso65x63ayLEvXrl1TYmJip7WuDTGjRo3SoEGDVFtbG3J/XV2d4uPj29RHRUUpKioq5L6vfe1rvdZPTEyMq/6T3Yht1DVsp86xjTrHNuoc26hr3LidvF5vl+pcO7E3MjJSaWlpKisrC7m/rKxMmZmZDnUFAADcwrUjMZK0cuVK5eXlaeLEicrIyNC2bdt08eJFLV682OnWAACAw1wdYubOnaurV6/qn//5n1VTU6OUlBS9+eabGjNmTL/1EBUVpV/84hdtDlXhr9hGXcN26hzbqHNso86xjbomHLaTx7K6cg4TAACAu7h2TgwAAEBHCDEAAMBIhBgAAGAkQgwAADASIaYTL7zwgpKTkzVkyBClpaXp/ff5Nt5bvffee5o5c6YSExPl8Xi0b98+p1tylaKiIj388MOKjo5WXFycZs2apXPnzjndlqts2bJFDzzwgH3BrYyMDL311ltOt+VqRUVF8ng8ys/Pd7oVVykoKJDH4wlZfD6f0225zqeffqq///u/18iRIzVs2DB95zvfUWVlpdNt9QghpgOvvvqq8vPztW7dOn3wwQf63ve+p+zsbF28eNHp1lyjqalJEyZMUHFxsdOtuFJ5ebmWLl2qiooKlZWV6YsvvlBWVpaampqcbs01Ro8ereeee04nT57UyZMn9fjjj+sHP/iBzpw543RrrnTixAlt27ZNDzzwgNOtuNK3v/1t1dTU2MupU6ecbslV6uvr9d3vfleDBw/WW2+9pY8++kjr16/v1Svc9ydOse5Aenq6HnroIW3ZssW+b/z48Zo1a5aKiooc7MydPB6P9u7dq1mzZjndimtduXJFcXFxKi8v16OPPup0O64VGxurf/u3f9OCBQucbsVVGhsb9dBDD+mFF17Qs88+q+985zvatGmT0225RkFBgfbt26eqqiqnW3GtNWvW6He/+13YHFVgJKYdLS0tqqysVFZWVsj9WVlZOnLkiENdwXR+v1/Sl2/SaKu1tVUlJSVqampSRkaG0+24ztKlS/X9739f06ZNc7oV1zp//rwSExOVnJysH/3oR/rkk0+cbslV9u/fr4kTJ+pv/uZvFBcXpwcffFDbt293uq0eI8S0449//KNaW1vbfNlkfHx8my+lBLrCsiytXLlSjzzyiFJSUpxux1VOnTqlr371q4qKitLixYu1d+9e3X///U635SolJSX6n//5H0aBO5Cenq6XX35Zb7/9trZv367a2lplZmbq6tWrTrfmGp988om2bNmisWPH6u2339bixYu1YsUKvfzyy0631iOu/toBN/B4PCG3Lctqcx/QFcuWLdOHH36ow4cPO92K64wbN05VVVVqaGjQf//3f2v+/PkqLy8nyPxFdXW1fv7zn+vAgQMaMmSI0+24VnZ2tv3v1NRUZWRk6Bvf+IZ27typlStXOtiZe9y4cUMTJ05UYWGhJOnBBx/UmTNntGXLFv3DP/yDw911HyMx7Rg1apQGDRrUZtSlrq6uzegM0Jnly5dr//79OnTokEaPHu10O64TGRmpb37zm5o4caKKioo0YcIE/fKXv3S6LdeorKxUXV2d0tLSFBERoYiICJWXl+vf//3fFRERodbWVqdbdKXhw4crNTVV58+fd7oV10hISGjz4WD8+PHGnrBCiGlHZGSk0tLSVFZWFnJ/WVmZMjMzHeoKprEsS8uWLdNrr72mgwcPKjk52emWjGBZloLBoNNtuMbUqVN16tQpVVVV2cvEiRP1d3/3d6qqqtKgQYOcbtGVgsGgzp49q4SEBKdbcY3vfve7bS7z8L//+7/9+sXKvYnDSR1YuXKl8vLyNHHiRGVkZGjbtm26ePGiFi9e7HRrrtHY2KiPP/7Yvn3hwgVVVVUpNjZW9957r4OducPSpUu1Z88evf7664qOjrZH9rxer4YOHepwd+7wzDPPKDs7W0lJSbp27ZpKSkr07rvvqrS01OnWXCM6OrrNPKrhw4dr5MiRzK+6xerVqzVz5kzde++9qqur07PPPqtAIKD58+c73Zpr/OM//qMyMzNVWFioOXPm6Pjx49q2bZu2bdvmdGs9Y6FDv/rVr6wxY8ZYkZGR1kMPPWSVl5c73ZKrHDp0yJLUZpk/f77TrbnCnbaNJOull15yujXX+PGPf2z/jd1zzz3W1KlTrQMHDjjdlutNnjzZ+vnPf+50G64yd+5cKyEhwRo8eLCVmJhozZ492zpz5ozTbbnOr3/9ayslJcWKioqyvvWtb1nbtm1zuqUe4zoxAADASMyJAQAARiLEAAAAIxFiAACAkQgxAADASIQYAABgJEIMAAAwEiEGAAAYiRADAACMRIgBAABGIsQAAAAjEWIAAICRCDEAAMBI/z/tYsSVfeuiRAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 \n",
    "print(\"similar to above, but for angles\")  #convention is angle[a][b] is from a to b\n",
    "uuAngle = [[0. for t in range(nHDs)] for t in range(nHDs)]\n",
    "\n",
    "pi = 3.141592653\n",
    "twoPi = pi*2.\n",
    "startTime = time.time()\n",
    "for t in populatedTractList:\n",
    "    if t %200 == 0:\n",
    "        print(\"working on unit-unit angles for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime)  )\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "            angLE = math.atan2(hdCP[tt].y - hdCP[t].y, xScale * (hdCP[tt].x - hdCP[t].x) )\n",
    "            uuAngle[t][tt], uuAngle[tt][t] = angLE % twoPi, (angLE + pi) % twoPi\n",
    "print(\"All done with angles; total elapsed seconds =\",int(time.time()-startTime) )\n",
    "plt.hist(uuAngle)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b198eb1a-7514-4c48-8a8b-9aac879e51fc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Colorado-only -- define a simple map hull and HD weights\n",
    "MAPhull = MAP.buffer(0.02)\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAPhull)\n",
    "plt.show()\n",
    "HDweight = [tractPop[t] / float(statePop) for t in range(nHDs)]\n",
    "aDP = float(statePop)/nDistricts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3214fdc5-d104-4164-9478-7ab097ce01e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\n",
      "For each Home District, we will consider a wedge as one-from-full when it is within 1486.1554697554698 of targetWedgePop\n",
      "I am working on HD number 0 of 3108 HDs.  Elapsed sec = 0\n",
      "I am working on HD number 200 of 3108 HDs.  Elapsed sec = 59\n",
      "I am working on HD number 400 of 3108 HDs.  Elapsed sec = 109\n",
      "I am working on HD number 600 of 3108 HDs.  Elapsed sec = 152\n",
      "I am working on HD number 800 of 3108 HDs.  Elapsed sec = 205\n",
      "I am working on HD number 1000 of 3108 HDs.  Elapsed sec = 262\n",
      "I am working on HD number 1200 of 3108 HDs.  Elapsed sec = 321\n",
      "I am working on HD number 1400 of 3108 HDs.  Elapsed sec = 371\n",
      "I am working on HD number 1600 of 3108 HDs.  Elapsed sec = 417\n",
      "I am working on HD number 1800 of 3108 HDs.  Elapsed sec = 468\n",
      "I am working on HD number 2000 of 3108 HDs.  Elapsed sec = 518\n",
      "I am working on HD number 2200 of 3108 HDs.  Elapsed sec = 562\n",
      "I am working on HD number 2400 of 3108 HDs.  Elapsed sec = 625\n",
      "I am working on HD number 2600 of 3108 HDs.  Elapsed sec = 667\n",
      "I am working on HD number 2800 of 3108 HDs.  Elapsed sec = 718\n",
      "I am working on HD number 3000 of 3108 HDs.  Elapsed sec = 764\n",
      "789.567 seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of unit usage.\n",
      "unit avg and sd usage are 0.99958 0.21904\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 .......\n",
    "# BELOW modified Dec23 to use inter-unit distances and angles, (counties still wedgeIntersxn) otherwise similar to HD2\n",
    "# --THIS ESSENTIALLY TAKES THE ORIGINAL TRACT-BASED HD centerpoints, and redraws HD2 districts after convexifying corners and convex_hull\n",
    "print(\"Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\") \n",
    "#this is a hybrid of HD2 and the organic code, in that all wedge tracts must be in a chain of neighboring counties\n",
    "#General sequence: draw 4 equi-angle wedges with random starting orientation.  If not all can fill a quarter aDP ...\n",
    "# ... find the closest map boundary point to the tract center point in the shortest wedge.  Orient the 0th wedge to face this point\n",
    "# ... determine the \"maxWedgePop\" for this short wedge and the other three wedges extended past the boundary\n",
    "# ...  if this results in only one short wedge, or opposing short wedges, adjust wedge angles\n",
    "# Regardless of whether we re-oriented or adjusted angles, compute each wedgePop for infinite radius\n",
    "#   ... then adjust other targetWedgePops if some found to be short.\n",
    "#   ... for non-shorted wedges, use bisection method to adjust radius to meet targetWedgePop\n",
    "#   ... once total HDpop within tolerance, add/subtract a tract fraction to fulfill HDpop\n",
    "#  create a list of fully used tracts per HD, save the tract# of the split tract and its fractional use\n",
    "#  Compute tractUse across all HDs at the end from the tractUsageLists.  Defer patching and partisan calcs to another code\n",
    "\n",
    "pi=3.1415926536\n",
    "#MAPhull = MAP.convex_hull #used for exitAngle calc.  Defined in an above block to allow user modification\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2.*pi / nWedges\n",
    "angle, angle2, wedgePoly = [0.]*nWedges, [0.]*nWedges, [dummyPoly]*nWedges  #start and stop angle of each wedge\n",
    "pt1, pt2, pt3 = [Point(0,0)]*nWedges, [Point(0,0)]*nWedges, [Point(0,0)]*nWedges #these four define the polygon wedge for a growing home district\n",
    "tractUse = [0.] * nHDs  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "HDtractList = [list()]*nHDs\n",
    "splitTractNo = [-999]*nHDs  #the tract that is only partially used to finish each HD\n",
    "splitTractUse = [0.]*nHDs  #and this is what fraction of the split tract is included\n",
    "HDvPop = [0.]*nHDs\n",
    "#HDweight = [tractPop[t] / (statePop - excludedPop) for t in range(nTracts)]  #relative weight of each drawn HD\n",
    "HDPoly1 = [dummyPoly]*nHDs  #final 4-wedge shape, unionized from blockgroups / tracts\n",
    "HDarea = [0.]*nHDs  #geographical area of each home district (after boundary trim)\n",
    "HDradius = [[0.]*nWedges for t in range(nHDs)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nHDs)] #final starting angle for each HD wedge\n",
    "angle0 = [-999.] * nHDs  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "avgTractPop = statePop/nHDs\n",
    "tolerPops = [0.8 * avgTractPop, 0.5 * np.max(tractPop)]  #threshold gap before adding one more unit to a wedge \n",
    "tolerPop = tolerPops[0]\n",
    "print(\"For each Home District, we will consider a wedge as one-from-full when it is within\",tolerPops[0],\"of targetWedgePop\")\n",
    "tractPrintInterval = 200  #for tracking progress\n",
    "levelL = 0.36 #sqrt(pop) for angle=std  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "maxAngleRatio = 1.9  #for tightening tract weighting near boundaries  #HD2\n",
    "maxAngle = 1.8*pi/2. # limit to avoid wedges too close to half a pie\n",
    "minAdjRatio = 0.5  #min ratio of pop of adjacent wedge (to min wedge) to targetWedgePop to not consider this a corner HD\n",
    "maxUncap = 0.5 #the max ratio of uncaptured pop in a maxWedge vs. target wedge pop that we will not stretch to include (7/23)\n",
    "oppWt = 0.0    #the fraction of gap between normal targetWedgePop and the minWedgePop that we allow the opposite wedge to add to tgtPop = minWedgePop\n",
    "maxWedgePop = [0.] * nWedges  #wedge pop if we explode wedge to maximum radius\n",
    "printDebug = \"no\"\n",
    "codeStartTime = time.time()\n",
    "hdCPpop = [HDweight[t] * statePop for t in range(nHDs)]\n",
    "countyHDlist = [list() for c in range(nCounties)]\n",
    "for t in populatedTractList:\n",
    "    countyHDlist[HDcountyNo[t]].append(t)\n",
    "\n",
    "for t in populatedTractList:  #range(nTracts) : #loop on each tract. \n",
    "    hC = HDcountyNo[t]     #this tract's home county\n",
    "    HDtractList[t] = [t] #seed the list of tracts in this HD\n",
    "    wedgeList = [list() for w in range(nWedges)]   #list of each wedge's tracts, excluding home tract\n",
    "    barredList = list()  #list of wedge numbers for which we are barred from altering their targetWedgePops\n",
    "    if (t % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on HD number {0} of {1} HDs.  Elapsed sec = {2}\".format(t,nHDs,int(time.time()-codeStartTime) ) )  \n",
    "    nActiveWedges = nWedges #active wedges have not run over boundary\n",
    "    wedgePop = [0.]*nWedges\n",
    "    targetWedgePop = [aDP / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    \n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to the midangle of our starting wedge\n",
    "    wedgeAngle = [avgWedgeAngle for w in range(nWedges) ] #reset to equi-angle when starting each tract\n",
    "    for nW in range(nWedges-1):\n",
    "        wedgeAngle[nW] += random.uniform(-0.0001,0.0001)  #this wiggle solves a later indexing ambiguity for corner tracts\n",
    "    wedgeAngle[nWedges-1] = 2.*pi - (np.sum(wedgeAngle) - wedgeAngle[nWedges-1] ) #squaring up to 2pi total\n",
    "    startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "    for nW in range(1,nWedges):\n",
    "        startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "    endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "    #  TRIAL LOOP TO SEE WHICH WEDGES CAN FILL TO TARGET POP w/equiangle wedges\n",
    "    maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]    \n",
    "    maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "    willFill = [0] * nWedges #would this wedge meet its target with infinite radius?\n",
    "    for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "        iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "        #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList) \n",
    "        nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                neighborCountyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "        maxWedgePop[nW] += (iCP + nonCP)\n",
    "        wedgeList[nW] = Li + Ln\n",
    "        if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "            willFill[nW] = 1\n",
    "     \n",
    "    if np.sum(willFill) < nWedges:  #at least one wedge couldn't reach its wedgePop target (went over boundary) ...\n",
    "        minW = maxWedgePop.index(np.min(maxWedgePop)) #.. so we will orient the 0th wedge to face the shortest wedgePop's closest boundary\n",
    "        exitAngle = getExitAngle(hdCP[t],maxWedgePoly[minW], MAPhull, startAngle[minW], endAngle[minW])\n",
    "        angle0[t] = exitAngle - 0.5*(2.*pi / nWedges)  #Now reset all angles based on new starting orientation.  All wedge angles still equal\n",
    "        startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "        for nW in range(1,nWedges):\n",
    "            startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "        endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "        maxWedgePoly = [buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]\n",
    "        \n",
    "        willFill = [0]*nWedges\n",
    "        #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation (wedge angles still constant)\n",
    "        maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop        \n",
    "        for nW in range(nWedges):   #... then add in-county and nonCounty wedge Pop from contiguous chain of counties\n",
    "            iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "            #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "            nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                    neighborCountyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "            maxWedgePop[nW] += (iCP + nonCP)\n",
    "            wedgeList[nW] = Li + Ln\n",
    "            if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                willFill[nW] = 1       \n",
    "    \n",
    "    if np.sum(willFill) < nWedges:  #check if we need to modify wedge angles after possible re-orientation.  \n",
    "        # If so, re-draw maxWedgePoly's, re-calc maxWedgePops\n",
    "        nUnfilledWedges = nWedges - np.sum(willFill)\n",
    "        isChange, newInclA = getNewAngles(maxWedgePop, targetWedgePop, aDP, levelL, minAdjRatio, maxAngle, maxAngleRatio, nUnfilledWedges )\n",
    "        if isChange: #no longer equi-angle\n",
    "            newStartAngle = [0.5*(startAngle[nW]+endAngle[nW]) - 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            newEndAngle =   [0.5*(startAngle[nW]+endAngle[nW]) + 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            startAngle, endAngle, wedgeAngle = newStartAngle.copy(), newEndAngle.copy(), newInclA.copy()\n",
    "            maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], \n",
    "                                        maxD/math.cos(0.5*wedgeAngle[nW]), xScale ) for nW in range(nWedges) ]\n",
    "            willFill = [0]*nWedges\n",
    "            #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation and new wedge angles\n",
    "            maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "            for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "                iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])                \n",
    "                #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "                nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                        neighborCountyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "                maxWedgePop[nW] += (iCP + nonCP)\n",
    "                wedgeList[nW] = Li + Ln\n",
    "            minW = wedgeAngle.index(np.max(wedgeAngle)) #should be 0th wedge, but playing it safe.  This is the 1st wide-angle wedge ..\n",
    "            oppW = int(int(minW+nWedges/2)%nWedges)   #and its opposite\n",
    "            if maxWedgePop[minW] > maxWedgePop[oppW] and maxWedgePop[oppW] < aDP / nWedges:  #minW and oppW are flipped after inclA adjmt\n",
    "                oppW = minW\n",
    "                minW = int(int(minW+nWedges/2)%nWedges)\n",
    "            if maxWedgePop[minW] < targetWedgePop[oppW]:  #we need to constrain oppW in this HD2 implementation; redistribute tgt to adjacents\n",
    "                maxNonOppW = np.sum(maxWedgePop) - maxWedgePop[oppW] #...but only if other wedges can pick up slack; need to check\n",
    "                minOppWedgePop = aDP - maxNonOppW  #cannot set oppW target below this or we won't reach aDP across all wedges\n",
    "                barredList = [oppW]\n",
    "                targetWedgePop[oppW] = max(minOppWedgePop, maxWedgePop[minW] + oppWt * (targetWedgePop[oppW] - maxWedgePop[minW]) )\n",
    "                tWPgap = aDP / float(nWedges) - targetWedgePop[oppW] \n",
    "                for nW in range(nWedges):\n",
    "                    if nW != minW and nW != oppW:\n",
    "                        targetWedgePop[nW] += tWPgap/float(nWedges - 2.)  #if oppW target is limited, allot to adjacent wedges\n",
    "            for nW in range(nWedges):\n",
    "                if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                    willFill[nW] = 1  \n",
    "    \n",
    "    if abs(np.sum(targetWedgePop) / aDP - 1.) > 0.001:\n",
    "        raise Exception(\"FAIL! Our target wedgepops\",targetWedgePop, np.sum(targetWedgePop),\"no longer add up to\",aDP)\n",
    "    \n",
    "    if np.sum(willFill) == nWedges:  #all wedges will fill.  Will any leave a small near-boundary remnant?  If so, pick up smallest remnant\n",
    "        remnantWedgePopFrac = [ ( maxWedgePop[w] - targetWedgePop[w] )/targetWedgePop[w] for w in range(nWedges) ]\n",
    "        if np.min(remnantWedgePopFrac) < maxUncap :  #lessen tWP's of *adjacent* wedges, then increase this wedge's target --> max\n",
    "            minW = remnantWedgePopFrac.index(np.min(remnantWedgePopFrac))\n",
    "            oppW = int((minW+nWedges/2)%nWedges)\n",
    "            #print(\"filling to boundary for tract,wedge, tWP, mWP =\",t,minW, r3(targetWedgePop[minW]), maxWedgePop[minW])\n",
    "            for nW in range(nWedges):\n",
    "                if nW != minW and nW != oppW:\n",
    "                    targetWedgePop[nW] -= (remnantWedgePopFrac[minW] * targetWedgePop[minW] ) / (nWedges - 2.)\n",
    "            targetWedgePop[minW] = maxWedgePop[minW]\n",
    "            #       OK, READY TO SOLVE FOR NON-FILLED WEDGE SIZES once we adjust targets for unfilled wedges\n",
    "    #print(t,\" prior to rebalanceTWP call, mWPs, tWPs are\",maxWedgePop, targetWedgePop)\n",
    "    targetWedgePop, willFill = rebalanceTWPs(maxWedgePop, targetWedgePop, barredList)\n",
    "    #if np.max(targetWedgePop) - np.min(targetWedgePop) > 0.02 * aDP: #debug\n",
    "    #    print(\"for tract\",t,\",  After rebalancing but before tweaks for blocky pop adds: willFill, targetWedgePops and maxWedgePops are ...\")\n",
    "    #    for w in range(nWedges):\n",
    "    #        print(w, willFill[w],r3(targetWedgePop[w]),int(maxWedgePop[w]) )\n",
    "    for w in range(nWedges):  #WHEW!  WE CAN FINALLY ASSIGN ALL WEDGES' POPS AND TRACTLISTS\n",
    "        loop = 0\n",
    "        if willFill[w] == 0:  #wedge is maxed out\n",
    "            wedgePop[w] = maxWedgePop[w]\n",
    "            #wedgeList[w] = ...  #we already captured this list = maxWedge list\n",
    "            HDradius[t][w] = maxD/math.cos(0.5*wedgeAngle[w])\n",
    "        else:  #need to solve for wedge radius to meet targetPop.  Use bisection as scipy minimize no faster\n",
    "            HDcpWP = hdCPpop[t] * wedgeAngle[w]/(2.*pi)\n",
    "            nonHDcpTWP = targetWedgePop[w] - HDcpWP\n",
    "            #wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeB(nontractTWP,t,hC,maxWedgePoly[w],tolerPop,tractCP, tractPop,\n",
    "            #                                                        countyNo,countyTractList,countyGeom, neighborCountyList,uuDist[t])\n",
    "            wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeC(nonHDcpTWP,t,hC, maxWedgePoly[w],startAngle[w], endAngle[w], tolerPop,\n",
    "                                                                    hdCP, hdCPpop,HDcountyNo, countyHDlist,countyGeom,\n",
    "                                                                    neighborCountyList,uuDist[t],uuAngle[t])\n",
    "            popGap = nonHDcpTWP - wedgePop[w]  #gap between target and solved wedge pop; can be negative\n",
    "            notYetAdjusted, nextW = True, w+1  #looking to adjust a later wedge's target pop to minimize drift in total HD pop\n",
    "            while notYetAdjusted and nextW < nWedges:\n",
    "                if willFill[nextW] == 1 and maxWedgePop[nextW] > targetWedgePop[nextW] + popGap :  #can accommodate\n",
    "                    targetWedgePop[nextW] += popGap\n",
    "                    notYetAdjusted = False\n",
    "                nextW +=1          \n",
    "\n",
    "        HDangle[t][w] = startAngle[w]\n",
    "    #print(t,\"tract. After TWP adjustment, targetWedgePops are\",targetWedgePop)\n",
    "    HDtractList[t] = [t]\n",
    "    totPop = hdCPpop[t]\n",
    "    for nW in range(nWedges):\n",
    "        for tt in wedgeList[nW]:\n",
    "            HDtractList[t].append(tt)  #building the list of tracts in the Home District  (we'll keep up with below changes)\n",
    "            totPop += hdCPpop[tt]\n",
    "    offsetPop = totPop - aDP  #we have solved for all wedge radii to get each within one tractPop of target ... \n",
    "    HDvPop[t] = totPop\n",
    "    #if offsetPop > 0:   #... now include a splitPoly to nail the avg District Pop\n",
    "    #    isOver = True  #we slightly overshot.  ID the farthest-away tract for split-jettison\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], hdCPpop, neighborList)\n",
    "    #    HDvPop[t] = totPop - (1. - splitTractUse[t]) * tractPop[splitTractNo[t]]\n",
    "    #if offsetPop < 0:\n",
    "    #    isOver = False  #we have undershot.  Pick up the nearest contiguous tract that can be split to fill the gap\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], tractPop, neighborList)\n",
    "    #    HDtractList[t].append(splitTractNo[t])\n",
    "    #    HDvPop[t] = totPop + splitTractUse[t]*tractPop[splitTractNo[t]]       \n",
    "    #if abs(1. - HDvPop[t]/aDP) > 0.005 :  #something went wrong with pop assignation for this HD\n",
    "    #    print(\"WARNING! Total Home District pop was\",HDvPop[t],\"vs target\",aDP,\"for tract\",t)   ##### hdCP topology not yet known; skip partial\n",
    "        \n",
    "    HDPoly1[t] = dummyPoly  #tractGeom[t] #skip constructing the HD poly shape.  Do compute area of the Home District, including final partial\n",
    "    HDarea[t] = 0.\n",
    "    for tt in HDtractList[t]:\n",
    "        if tt == splitTractNo[t]:\n",
    "            tractUse[tt] += nDistricts * HDweight[t] * splitTractUse[t] \n",
    "            #HDarea[t]   += tractArea[tt] * splitTractUse[t]  #these are original (nonsquished) areas\n",
    "            \n",
    "        else:\n",
    "            tractUse[tt] += nDistricts * HDweight[t]\n",
    "            #HDarea[t]    += tractArea[tt]\n",
    "            #HDPoly1[t] = HDPoly1[t].union(tractGeom[tt])\n",
    "    HDPoly1[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t] )\n",
    "    #HDarea[t] = HDPoly1[t].area + splitTractUse[t] * tractArea[splitTractNo[t]]  \n",
    "    #if splitTractUse[t] > 0.5:\n",
    "    #    HDPoly1[t] = HDPoly1[t].union(tractGeom[splitTractNo[t]])\n",
    "                          \n",
    "    #ALL DONE ESTABLISHING THE FINAL HDTRACTLIST.  FINALIZE STATS\n",
    "totalTime = time.time() - codeStartTime\n",
    "print(r3(totalTime),\"seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of unit usage.\")\n",
    "n_bins=50\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"unit avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()\n",
    "HDvPop = [np.sum([hdCPpop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.scatter([hdCPpop[t] for t in populatedTractList],[HDvPop[t] for t in populatedTractList] )\n",
    "print(\"here are your HD pops\")\n",
    "plt.show()\n",
    "origHDHDtractList = [HDtractList[t].copy() for t in range(nHDs)] #save for posterity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4d4a50e6-17b7-41e5-a5da-523bbbebdeb4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit avg and sd usage are 0.99958 0.21904\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#results of option 2 .......\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"unit avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "23d8f96e-8d61-4fdc-8e27-c70b0dffa622",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hdCPx, hdCPy = [hdCP[t].x for t in range(nHDs)], [hdCP[t].y for t in range(nHDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "aec0cf55-112b-4eba-93c6-9cf1d1b87aae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we will write the polygon-based results to a file\n"
     ]
    }
   ],
   "source": [
    "#last block of option 2 (generating polygonal HDs from scratch)\n",
    "print(\"Now we will write the polygon-based results to a file\")\n",
    "tractNo = [t for t in range(nHDs) ]\n",
    "HDangle0 = [HDangle[t][0] for t in range(nHDs) ]\n",
    "HDangle1 = [HDangle[t][1] for t in range(nHDs) ]\n",
    "HDangle2 = [HDangle[t][2] for t in range(nHDs) ]\n",
    "HDangle3 = [HDangle[t][3] for t in range(nHDs) ]\n",
    "HDradius0 = [HDradius[t][0] for t in range(nHDs)]\n",
    "HDradius1 = [HDradius[t][1] for t in range(nHDs)]\n",
    "HDradius2 = [HDradius[t][2] for t in range(nHDs)]\n",
    "HDradius3 = [HDradius[t][3] for t in range(nHDs)]\n",
    "\n",
    "\n",
    "paramList = [\"STATE\",\"statePop\",\"nDistricts\",\"nHDs\",\"nWedges\",\"popn-toler\",\"levelL\", \"maxAngleRatio\",\n",
    "             \"maxAngle\",\"minAdjRatio\",\"maxUncap\", \"oppWt\", \"calc sec\",\"xScale\",\"outputs...\"]\n",
    "paramValues = [STATE,statePop, nDistricts, nHDs, nWedges, tolerPop, levelL, maxAngleRatio, maxAngle, minAdjRatio, maxUncap,\n",
    "               oppWt, totalTime, xScale, -777]\n",
    "for i in range(nHDs-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "HDdf = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"countyNo\":HDcountyNo,\n",
    "                    \"tractNo\":tractNo,\"centroid x\":hdCPx,\"centroid y\":hdCPy,\"tractPop\":hdCPpop,\n",
    "                    \"HDweight\":HDweight,\"HD-pop\":HDvPop,\"HDarea\":HDarea,\n",
    "                    \"startAngle\":angle0,\"HDangle0\":HDangle0,\"HDangle1\":HDangle1,\"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\n",
    "                    \"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\"HDradius2\":HDradius2, \"HDradius3\":HDradius3,\"tractUse\":tractUse,\n",
    "                    \"splitTractNo\":splitTractNo,\"splitTractUse\":splitTractUse,\"HDtractList\":HDtractList} ) \n",
    "\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Bnopatch\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeB\n",
    "outname = STATE+str(int(nHDs))+\"convexHD2\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeC\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Buutpatch\"+str(int(nDistricts))+\"nW4.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "HDdf.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "5cd3b565-5014-46f0-9c07-30a4d873f032",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "determining intersections with corner clusters\n",
      "299.0 intersections found\n",
      "0 cluster. It took 189 HDs to reach a district pop's worth of intersection.  last frac area was 0.16774\n",
      "280.0 intersections found\n",
      "1 cluster. It took 199 HDs to reach a district pop's worth of intersection.  last frac area was 0.23727\n",
      "193.0 intersections found\n",
      "2 cluster. It took 191 HDs to reach a district pop's worth of intersection.  last frac area was 0.00095\n"
     ]
    }
   ],
   "source": [
    "#I believe this is still option-2 only\n",
    "print(\"determining intersections with corner clusters\")\n",
    "for i in range(len(CCBgeom)):\n",
    "    nIntersect = 0.   \n",
    "    CCBareaPart = [0. for t in range(nHDs)]\n",
    "    for t in range(nHDs):\n",
    "        area = HDPoly1[t].intersection(CCBgeom[i]).area\n",
    "        CCBareaPart[t] = area / CCBarea[i]\n",
    "        if area > 0:\n",
    "            nIntersect +=1\n",
    "    print(nIntersect,\"intersections found\")\n",
    "\n",
    "    idx = np.argsort(CCBareaPart)\n",
    "    j, foundFrac, foundPop = 0, 0., 0.\n",
    "    while foundPop < aDP and j < nHDs:\n",
    "        j +=1\n",
    "        jj = idx[nHDs - j]\n",
    "        foundFrac += HDweight[jj] * nDistricts*CCBareaPart[jj]\n",
    "        foundPop += hdCPpop[jj]\n",
    "    print(i,\"cluster. It took\",j,\"HDs to reach a district pop's worth of intersection.  last frac area was\",r5(CCBareaPart[jj]) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b376b42c-bccd-42a2-9131-0dd07915d5d0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b7a38aff-e4c4-498a-9f63-b6d5d02ab158",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "print(np.average(HDweight) * nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "253554da-8842-470e-b9b3-5626823059b0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's ensure normalization of each cluster's usage based on how much of its area must be captured to consider a cluster captured\n",
      "working on cluster no -1 containing counties [2, 43, 73, 1, 112, 37, 10]\n",
      "halfway there! last use was 0.6811\n",
      "our final fractional capture area to normalize this cluster's usage is 0.12481\n",
      "working on cluster no 0 containing counties [59, 72, 4]\n",
      "halfway there! last use was 0.89106\n",
      "our final fractional capture area to normalize this cluster's usage is 0.37006\n",
      "working on cluster no 1 containing counties [66, 99, 71, 102, 77, 34]\n",
      "halfway there! last use was 0.66577\n",
      "our final fractional capture area to normalize this cluster's usage is 0.02696\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#I THINK I SKIP THIS IF I ALREADY CREATED HDVTDLIST'S FROM POLYGONS ??\n",
    "print(\"Let's ensure normalization of each cluster's usage based on how much of its area must be captured to consider a cluster captured\")\n",
    "#origHDlist = [list() for t in range(nHDs)],\n",
    "splitTractNo, splitTractUse = [-999]*nHDs, [0.]*nHDs\n",
    "origHDpop = [0. for t in range(nHDs)]  #these will be based on captured Census vtd's\n",
    "HDpoly, HDdiam = [dummyPoly for t in range(nHDs)], [0. for t in range(nHDs)]\n",
    "\n",
    "popHDlist = list()  #rebuild here again with the geometries\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001 :  #HD poly was actually drawn  #[(HDradius[t][w]+0.001*maxD) for w in range(4)]\n",
    "        HDpoly[t] = buildPoly(hdCP[t], HDradius[t], HDangle[t])  #expand to catch the units on HD edge\n",
    "        HDdiam[t] = HDpoly[t].area **0.5  #approximate, for later scoring purposes of underuse * distance\n",
    "        popHDlist.append(t)\n",
    "\n",
    "\n",
    "CCBuse, CCBareaFrac, CCBarea = [0. for CCB in CCBlist], [0.5 for CCB in CCBlist], [geo.area for geo in CCBgeom]\n",
    "for j,geo in enumerate(CCBgeom):\n",
    "    print(\"working on cluster no\",j-1,\"containing counties\",CCBlist[j] )\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    HDfrac = [ 0. for t in range(nHDs) ]\n",
    "    for t in range(nHDs):\n",
    "        if HDcountyNo[t] in CCBlist[j]:\n",
    "            HDfrac[t] = 1.\n",
    "        else:\n",
    "            HDfrac[t] = HDpoly[t].intersection(geo).area / CCBarea[j]\n",
    "    idx = np.argsort(HDfrac)\n",
    "    i = nHDs\n",
    "    while CCBuse[j] < 1.000 - 0.5 * nDistricts*np.average(HDweight) and i > 0:\n",
    "        i -=1\n",
    "        t = idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        if CCBuse[j] > 0.5 and CCBuse[j] - HDweight[t] * nDistricts < 0.5:\n",
    "            print(\"halfway there! last use was\",r5(HDfrac[t]))\n",
    "            plotPoly(HDpoly[t],0.2)\n",
    "        #origHDlist[t].append(unitNo)  #postpone this until main loop\n",
    "        #origHDpop[t] += CCBpop[j]     #postpone until main\n",
    "    if i <= 1:\n",
    "        print(\"WARNING, only\",r5(CCBuse[j]),\" of a district's worth of ensemble intersected the cluster geometry\")\n",
    "        # Add more stuff here to inflate the poly and try again ...\n",
    "    else:\n",
    "        CCBareaFrac[j] = HDfrac[t]\n",
    "        print(\"our final fractional capture area to normalize this cluster's usage is\",r5(CCBareaFrac[j]) )\n",
    "        plotPoly(MAP,0.2)\n",
    "        plotPoly(geo,0.8)\n",
    "        plotCenter(j,geo)\n",
    "        plotPoly(HDpoly[t],1.3)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fe19092b-1ec7-4394-b148-5aece7575363",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's see how these area fracs play out for unit counties -- but don't add their pops to HDlists just yet ...\n",
      "working on county 22\n",
      "working on county 100\n",
      "Across all unit counties, Here is a histogram of county area we must capture to normalize county usage\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Let's see how these area fracs play out for unit counties -- but don't add their pops to HDlists just yet ...\")\n",
    "unitCuse, unitCareaFrac, unitCarea = [0. for c in unitCounties], [0.5 for c in unitCounties], [countyGeom[c].area for c in unitCounties]\n",
    "for j,c in enumerate(unitCounties):\n",
    "    unitNo = allUnits.index(c+0.5)\n",
    "    if j%10 == 0:\n",
    "        print(\"working on county\",c)\n",
    "    HDfrac = [ HDpoly[t].intersection(countyGeom[c]).area / unitCarea[j] for t in range(nHDs) ]\n",
    "    idx = np.argsort(HDfrac)\n",
    "    i = nHDs\n",
    "    while unitCuse[j] < 1.000 - 0.5 * nDistricts*np.average(HDweight) and i > 0:\n",
    "        i -=1\n",
    "        t = idx[i]\n",
    "        unitCuse[j] += HDweight[t] * nDistricts\n",
    "        #origHDlist[t].append(unitNo)\n",
    "        #origHDpop[t] += unitPop[unitNo]\n",
    "    if i <= 1:\n",
    "        print(\"WARNING, only\",r5(unitCuse[j]),\" of a district's worth of ensemble intersected the county geometry\")\n",
    "        # This shouldn't happen.  But if does, add more stuff here to inflate the poly and try again ...\n",
    "    else:\n",
    "        unitCareaFrac[j] = HDfrac[t]\n",
    "        #print(\"our final fractional capture area to normalize this cluster's usage is\",r5(unitCareaFrac[j]) )\n",
    "print(\"Across all unit counties, Here is a histogram of county area we must capture to normalize county usage\")\n",
    "plt.hist(unitCareaFrac,bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "fdbc6b9c-2ef8-4b00-b106-079ee1713366",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the thresholds of captured county area to set unit county usage to unity\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Here are the thresholds of captured county area to set unit county usage to unity\")\n",
    "for i, c in enumerate(unitCounties):\n",
    "    plotCenter(round(unitCareaFrac[i],2), countyGeom[c],8)\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "6c93bff3-ca27-4fcb-bd83-1f7d709c248b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing vtdlist for patching\n",
      "Must have already established unitGeoms, pops, topology\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched vtdlist, e.g. ./state_HD_output/CO8HDpcL18Sepfrom14Seppatched.csv ./state_HD_output/CO8HDpcL18Sepfrom14Seppatched.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I read in 3108 HD lists of vtds\n"
     ]
    }
   ],
   "source": [
    "#ALTERNATE FOR CO ONLY -- OUR STARTER FILE IS NOT HD SHAPES BUT VTD LISTS\n",
    "\n",
    "print(\"this optional RESTART block pulls in an existing vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology\")\n",
    "infile = input(\"enter the unpatched vtdlist, e.g. ./state_HD_output/CO8HDpcL18Sepfrom14Seppatched.csv\")\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDtractList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDwt\"]\n",
    "HDvPop = inDF[\"HD-pop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of vtds\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "7e77e40f-2b30-455a-a5bf-be0d3e35588a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wc0OhkJ566inNmzdP06ZNU2VlZcycxsZGORyOmOuLL76IpzwAADDF2A4sgUBAlZWVqqmpUTAYVElJicrKytTd3T3k/IGBAc2aNUs1NTXKz88fdl23261QKBR1uVwuu+UBAIApyHZgefPNN7V+/Xo9++yzmj9/vrZv366srCzV19cPOX/u3LnasWOH1q5dK4/HM+y6DodDGRkZURcAAIBkM7BcvXpVnZ2dKi0tjRovLS1Ve3v7LRVy5coVZWdna86cOXryyScVDAZHnD8wMKBwOBx1AQCAqclWYOnr69Pg4KDS09OjxtPT09Xb2xt3Ebm5uWpsbNSRI0fU1NQkl8ulJUuW6JNPPhn2ntraWnk8nsiVlZUV9/cHAABmi+tNtw6HI+qxZVkxY3YUFRXp6aefVn5+vkpKSvTee+/pgQce0FtvvTXsPdXV1erv749cPT09cX9/AABgtmQ7k9PS0pSUlBSzm3LhwoWYXZdbMW3aND388MMj7rA4nU45nc4x+54AAMBctnZYUlJS5PV61dLSEjXe0tKi4uLiMSvKsix1dXUpMzNzzNYEAACTl60dFkmqqqpSeXm5CgoK5PP51NDQoO7ublVUVEi68VLN+fPntW/fvsg9XV1dkm68sfazzz5TV1eXUlJSlJeXJ0naunWrioqK9M1vflPhcFg7d+5UV1eXdu3aNQYtAgCAyc52YPH7/bp48aK2bdumUCikBQsWqLm5WdnZ2ZJuHBT39TNZFi5cGPnnzs5O7d+/X9nZ2Tp37pwk6dKlS3r++efV29srj8ejhQsXqrW1VYsXL76F1gAAwFThsCzLSnQRYyEcDsvj8ai/v19utzvR5eA2MnfTh4ku4bZw7rUViS4BwDgY7fM3nyUEAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeMmJLgD4ytxNHya6BACAodhhAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHjJiS4AAEZj7qYPE12CbedeW5HoEoApgx0WAABgvLgCS11dnXJycuRyueT1etXW1jbs3FAopKeeekrz5s3TtGnTVFlZOeS8gwcPKi8vT06nU3l5eTp06FA8pQEAgCnIdmAJBAKqrKxUTU2NgsGgSkpKVFZWpu7u7iHnDwwMaNasWaqpqVF+fv6Qczo6OuT3+1VeXq7Tp0+rvLxca9as0ccff2y3PAAAMAU5LMuy7NxQWFioRYsWqb6+PjI2f/58rV69WrW1tSPe+wd/8Ad66KGHtH379qhxv9+vcDiso0ePRsYef/xx3X333WpqahpVXeFwWB6PR/39/XK73aNvCMaYjO9RAEbCe1iAmxvt87etHZarV6+qs7NTpaWlUeOlpaVqb2+Pr1Ld2GH5+prLly8fcc2BgQGFw+GoCwAATE22AktfX58GBweVnp4eNZ6enq7e3t64i+jt7bW9Zm1trTweT+TKysqK+/sDAACzxfWmW4fDEfXYsqyYsfFes7q6Wv39/ZGrp6fnlr4/AAAwl61zWNLS0pSUlBSz83HhwoWYHRI7MjIybK/pdDrldDrj/p4AAGDysLXDkpKSIq/Xq5aWlqjxlpYWFRcXx12Ez+eLWfP48eO3tCYAAJg6bJ90W1VVpfLychUUFMjn86mhoUHd3d2qqKiQdOOlmvPnz2vfvn2Re7q6uiRJV65c0Weffaauri6lpKQoLy9PkrRx40Y98sgjev3117Vq1SodPnxYH330kU6ePDkGLQIAgMnOdmDx+/26ePGitm3bplAopAULFqi5uVnZ2dmSbhwU9/UzWRYuXBj5587OTu3fv1/Z2dk6d+6cJKm4uFgHDhzQ5s2b9corr+j+++9XIBBQYWHhLbQGAACmCtvnsJiKc1gmP85hwVTDOSzAzY3LOSwAAACJQGABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA48UVWOrq6pSTkyOXyyWv16u2trYR5584cUJer1cul0v33Xefdu/eHfX1xsZGORyOmOuLL76IpzwAADDF2A4sgUBAlZWVqqmpUTAYVElJicrKytTd3T3k/LNnz+qJJ55QSUmJgsGgXn75Zb344os6ePBg1Dy3261QKBR1uVyu+LoCAABTisOyLMvODYWFhVq0aJHq6+sjY/Pnz9fq1atVW1sbM/+HP/yhjhw5ojNnzkTGKioqdPr0aXV0dEi6scNSWVmpS5cuxdmGFA6H5fF41N/fL7fbHfc6SJy5mz5MdAnAbe/caysSXQJuM6N9/ra1w3L16lV1dnaqtLQ0ary0tFTt7e1D3tPR0REzf/ny5Tp16pS+/PLLyNiVK1eUnZ2tOXPm6Mknn1QwGLRTGgAAmMJsBZa+vj4NDg4qPT09ajw9PV29vb1D3tPb2zvk/GvXrqmvr0+SlJubq8bGRh05ckRNTU1yuVxasmSJPvnkk2FrGRgYUDgcjroAAMDUFNebbh0OR9Rjy7Jixm42//fHi4qK9PTTTys/P18lJSV677339MADD+itt94ads3a2lp5PJ7IlZWVFU8rAABgErAVWNLS0pSUlBSzm3LhwoWYXZSvZGRkDDk/OTlZM2fOHLqoadP08MMPj7jDUl1drf7+/sjV09NjpxUAADCJ2AosKSkp8nq9amlpiRpvaWlRcXHxkPf4fL6Y+cePH1dBQYGmT58+5D2WZamrq0uZmZnD1uJ0OuV2u6MuAAAwNdl+Saiqqko//elPtXfvXp05c0YvvfSSuru7VVFRIenGzsfatWsj8ysqKvQ///M/qqqq0pkzZ7R3717t2bNHP/jBDyJztm7dqmPHjum///u/1dXVpfXr16urqyuyJgAAuL0l273B7/fr4sWL2rZtm0KhkBYsWKDm5mZlZ2dLkkKhUNSZLDk5OWpubtZLL72kXbt2afbs2dq5c6e+853vROZcunRJzz//vHp7e+XxeLRw4UK1trZq8eLFY9AiAACY7Gyfw2IqzmGZ/DiHBUA8ODtmchuXc1gAAAASgcACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjJec6AIAALgVczd9mOgSbDv32opElzDpEFgAAJhghCz7eEkIAAAYj8ACAACMR2ABAADGI7AAAADj8abbUeDNUQAAJBY7LAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxuPXmqeoyfir2AAADIcdFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMF1dgqaurU05Ojlwul7xer9ra2kacf+LECXm9XrlcLt13333avXt3zJyDBw8qLy9PTqdTeXl5OnToUDylAQCAKch2YAkEAqqsrFRNTY2CwaBKSkpUVlam7u7uIeefPXtWTzzxhEpKShQMBvXyyy/rxRdf1MGDByNzOjo65Pf7VV5ertOnT6u8vFxr1qzRxx9/HH9nAABgynBYlmXZuaGwsFCLFi1SfX19ZGz+/PlavXq1amtrY+b/8Ic/1JEjR3TmzJnIWEVFhU6fPq2Ojg5Jkt/vVzgc1tGjRyNzHn/8cd19991qamoaVV3hcFgej0f9/f1yu912WrqpuZs+HNP1AACYbM69tmJc1h3t83eynUWvXr2qzs5Obdq0KWq8tLRU7e3tQ97T0dGh0tLSqLHly5drz549+vLLLzV9+nR1dHTopZdeipmzffv2YWsZGBjQwMBA5HF/f7+kG42PtesDvxvzNQEAmEzG4/n199e92f6JrcDS19enwcFBpaenR42np6ert7d3yHt6e3uHnH/t2jX19fUpMzNz2DnDrSlJtbW12rp1a8x4VlbWaNsBAACj5Nk+vutfvnxZHo9n2K/bCixfcTgcUY8ty4oZu9n8r4/bXbO6ulpVVVWRx9evX9f//u//aubMmSPeNx7C4bCysrLU09Mz5i9Hmex27Vuid3q/vXq/XfuW6H0iercsS5cvX9bs2bNHnGcrsKSlpSkpKSlm5+PChQsxOyRfycjIGHJ+cnKyZs6cOeKc4daUJKfTKafTGTV21113jbaVceF2u2+7P9DS7du3RO/0fnu5XfuW6H28ex9pZ+Urtn5LKCUlRV6vVy0tLVHjLS0tKi4uHvIen88XM//48eMqKCjQ9OnTR5wz3JoAAOD2YvsloaqqKpWXl6ugoEA+n08NDQ3q7u5WRUWFpBsv1Zw/f1779u2TdOM3gt5++21VVVXpueeeU0dHh/bs2RP12z8bN27UI488otdff12rVq3S4cOH9dFHH+nkyZNj1CYAAJjMbAcWv9+vixcvatu2bQqFQlqwYIGam5uVnZ0tSQqFQlFnsuTk5Ki5uVkvvfSSdu3apdmzZ2vnzp36zne+E5lTXFysAwcOaPPmzXrllVd0//33KxAIqLCwcAxaHH9Op1OvvvpqzEtUU93t2rdE7/R+e/V+u/Yt0btJvds+hwUAAGCi8VlCAADAeAQWAABgPAILAAAwHoEFAAAYj8AyCnV1dcrJyZHL5ZLX61VbW9uwc9etWyeHwxFzPfjggxNY8dix07skvfvuu8rPz9c3vvENZWZm6s///M918eLFCap2bNntfdeuXZo/f75SU1M1b968yK/2Tyatra1auXKlZs+eLYfDoX/4h3+46T0nTpyQ1+uVy+XSfffdp927d49/oePAbu+hUEhPPfWU5s2bp2nTpqmysnJC6hwPdnv/4IMPtGzZMs2aNUtut1s+n0/Hjh2bmGLHmN3eT548qSVLlmjmzJlKTU1Vbm6ufvKTn0xMsWMonv/Wv/Iv//IvSk5O1kMPPTRu9Q2FwHITgUBAlZWVqqmpUTAYVElJicrKyqJ+dfv37dixQ6FQKHL19PRoxowZ+tM//dMJrvzW2e395MmTWrt2rdavX69f/vKXev/99/Wv//qvevbZZye48ltnt/f6+npVV1dry5Yt+uUvf6mtW7dqw4YN+vnPfz7Bld+azz//XPn5+Xr77bdHNf/s2bN64oknVFJSomAwqJdfflkvvviiDh48OM6Vjj27vQ8MDGjWrFmqqalRfn7+OFc3vuz23traqmXLlqm5uVmdnZ169NFHtXLlSgWDwXGudOzZ7f2OO+7QCy+8oNbWVp05c0abN2/W5s2b1dDQMM6Vji27fX+lv79fa9eu1R/90R+NU2UjsDCixYsXWxUVFVFjubm51qZNm0Z1/6FDhyyHw2GdO3duPMobV3Z7/5u/+RvrvvvuixrbuXOnNWfOnHGrcbzY7d3n81k/+MEPosY2btxoLVmyZNxqHG+SrEOHDo045y//8i+t3NzcqLHvfe97VlFR0ThWNv5G0/vvW7p0qbVx48Zxq2ci2e39K3l5edbWrVvHvqAJFG/vf/zHf2w9/fTTY1/QBLHTt9/vtzZv3my9+uqrVn5+/rjW9XXssIzg6tWr6uzsVGlpadR4aWmp2tvbR7XGnj179Nhjj0UO1pss4um9uLhYv/nNb9Tc3CzLsvTpp5/q7//+77VixYqJKHnMxNP7wMCAXC5X1Fhqaqp+8Ytf6Msvvxy3WhOto6Mj5ue0fPlynTp1akr3jWjXr1/X5cuXNWPGjESXMuGCwaDa29u1dOnSRJcy7n72s5/pv/7rv/Tqq68m5PsTWEbQ19enwcHBmA9hTE9Pj/mwxqGEQiEdPXp0Ur4kEk/vxcXFevfdd+X3+5WSkqKMjAzdddddeuuttyai5DETT+/Lly/XT3/6U3V2dsqyLJ06dUp79+7Vl19+qb6+vokoOyF6e3uH/Dldu3ZtSveNaG+88YY+//xzrVmzJtGlTJg5c+bI6XSqoKBAGzZsmJT/n7fjk08+0aZNm/Tuu+8qOdn2IfljgsAyCg6HI+qxZVkxY0NpbGzUXXfdpdWrV49TZePPTu+/+tWv9OKLL+pHP/qROjs79Y//+I86e/Zs5HOmJhs7vb/yyisqKytTUVGRpk+frlWrVmndunWSpKSkpPEuNaGG+jkNNY6pqampSVu2bFEgENA999yT6HImTFtbm06dOqXdu3dr+/btUZ+PN9UMDg7qqaee0tatW/XAAw8krI7ExKRJIi0tTUlJSTF/q75w4ULM3yq/zrIs7d27V+Xl5UpJSRnPMsdFPL3X1tZqyZIl+ou/+AtJ0re//W3dcccdKikp0V/91V8pMzNz3OseC/H0npqaqr179+qdd97Rp59+qszMTDU0NOjOO+9UWlraRJSdEBkZGUP+nJKTkzVz5swEVYWJEggEtH79er3//vt67LHHEl3OhMrJyZEkfetb39Knn36qLVu26Lvf/W6Cqxofly9f1qlTpxQMBvXCCy9IuvEyoGVZSk5O1vHjx/WHf/iH414HOywjSElJkdfrVUtLS9R4S0uLiouLR7z3xIkT+vWvf63169ePZ4njJp7ef/e732natOg/Ul/tLliT6COrbuXf+/Tp0zVnzhwlJSXpwIEDevLJJ2N+JlOJz+eL+TkdP35cBQUFmj59eoKqwkRoamrSunXrtH///kn3PrWxZlmWBgYGEl3GuHG73fq3f/s3dXV1Ra6KigrNmzdPXV1dE/ZBxeyw3ERVVZXKy8tVUFAgn8+nhoYGdXd3R17mqK6u1vnz52PO3NizZ48KCwu1YMGCRJQ9Juz2vnLlSj333HOqr6/X8uXLFQqFVFlZqcWLF2v27NmJbMU2u73/53/+p37xi1+osLBQ//d//6c333xT//7v/66//du/TWQbtl25ckW//vWvI4/Pnj2rrq4uzZgxQ/fee29M3xUVFXr77bdVVVWl5557Th0dHdqzZ8+k3B6327skdXV1Re797LPP1NXVpZSUFOXl5U10+bfEbu9NTU1au3atduzYoaKiosguW2pqqjweT0J6iJfd3nft2qV7771Xubm5km4c5/DjH/9Y3//+9xNSf7zs9D1t2rSY57J77rlHLpdrYp/jJvR3kiapXbt2WdnZ2VZKSoq1aNEi68SJE5GvPfPMM9bSpUuj5l+6dMlKTU21GhoaJrjSsWe39507d1p5eXlWamqqlZmZaf3Zn/2Z9Zvf/GaCqx4bdnr/1a9+ZT300ENWamqq5Xa7rVWrVln/8R//kYCqb80//dM/WZJirmeeecayrKH/nf/zP/+ztXDhQislJcWaO3euVV9fP/GFj4F4eh9qfnZ29oTXfqvs9r506dIR508mdnvfuXOn9eCDD1rf+MY3LLfbbS1cuNCqq6uzBgcHE9NAnOL58/77EvFrzQ7LmkR79QAA4LY0dV9cBwAAUwaBBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADG+3+XzVkp96A5LwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#skip this special block\n",
    "vtdUse = [0. for v in range(nVTDs)]\n",
    "for t in range(nHDs):\n",
    "    for v in inVTDlist[t]:\n",
    "        vtdUse[v] += HDweight[t] * nDistricts\n",
    "plt.hist(vtdUse,weights=HDweight)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9829fb6c-36b2-4f75-aae4-0529f3eef61d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "special prework for CO since we drew HDs on whole vtds -- ID border counties and vtds\n"
     ]
    }
   ],
   "source": [
    "#skip this special block\n",
    "print(\"special prework for CO since we drew HDs on whole vtds -- ID border counties and vtds\")\n",
    "borderVTDs, borderCounties = list(), list()\n",
    "for c in range(nCounties):\n",
    "    if  countyGeom[c].intersects(MAP.exterior):\n",
    "        borderCounties.append(c)\n",
    "        for v in countyTractList[c]:\n",
    "            if vtdGeom[v].intersects(MAP.exterior):\n",
    "                borderVTDs.append(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "49192ae8-b644-4d7f-a7bc-0b6c8d1ba88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "since we are starting from a decent usage distro on VTDs, revert to units = vtds\n",
      "Now writing the master list of units, which may be individual vtd's (NOT whole counties, or corner county clusters for CO special)\n",
      "After surround checks, we appear to have 3103 building blocks defined.\n",
      "Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "working on unit neighbor lists for county 0\n",
      "I handled a surrounded vtd 2214 surrounded by vtd-unit 354 353 in county 16\n",
      "I handled a surrounded vtd 2215 surrounded by vtd-unit 479 478 in county 16\n",
      "I handled a surrounded vtd 2217 surrounded by vtd-unit 363 362 in county 16\n",
      "working on unit neighbor lists for county 20\n",
      "I handled a surrounded vtd 240 surrounded by vtd-unit 239 240 in county 26\n",
      "I handled a surrounded vtd 241 surrounded by vtd-unit 239 240 in county 26\n",
      "working on unit neighbor lists for county 40\n",
      "working on unit neighbor lists for county 60\n",
      "Whew, we now have a set of 3103  units (vtds,counties, clusters) and their neighbors to map onto polygonal Home Districts\n",
      "We resolved 5 VTDs that were surrounded by another VTD\n"
     ]
    }
   ],
   "source": [
    "#more CO-only when using no fused units\n",
    "print(\"since we are starting from a decent usage distro on VTDs, revert to units = vtds\")\n",
    "#HDunitList = [list() for t in range(nHDs)]\n",
    "unitCounties,allFusedCounties, CCBgeom = list(), list(), list()  #zero these out\n",
    "\n",
    "unitPop, unitCP, unitGeom, allUnits = list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#NOTE, WE DON'T ELIMINATE surroundees, we just disconnect them in neighborlists and xfer pops and geometries\n",
    "print(\"Now writing the master list of units, which may be individual vtd's (NOT whole counties, or corner county clusters for CO special)\")\n",
    "for c in range(nCounties):\n",
    "    if len(countyTractList[c]) == 1:\n",
    "        unitCounties.append(c)\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(countyGeom[c])\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "    if countyGeom[c].intersects(MAP.exterior): #c in borderCounties:\n",
    "        borderUnits.append(len(allUnits)-1)\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "for v in range(nVTDs):\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for vv in set(countyTractList[c]).difference({v}) :\n",
    "            if nVTDneighbors[v] > 1:  #as long as we find two, kick out.  Will do full neighbor list later\n",
    "                break\n",
    "            if vtdGeom[vv].intersects(vtdGeom[v]):\n",
    "                nVTDneighbors[v] +=1\n",
    "                lastVTDneighbor[v] = vv\n",
    "        if nVTDneighbors[v] < 2:\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if vtdGeom[v].intersects(countyGeom[cc]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    break  #any vtd that touches a county line can't be surrounded\n",
    "for v in range(nVTDs):\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties:    \n",
    "        if nVTDneighbors[v] > 1:\n",
    "            unitCP.append(tractCP[v])\n",
    "            unitPop.append(tractPop[v])\n",
    "            unitGeom.append(vtdGeom[v])\n",
    "            vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "            allUnits.append(v)\n",
    "for v in range(nVTDs):\n",
    "    if nVTDneighbors[v] == 1:\n",
    "        uu = allUnits.index(lastVTDneighbor[v])\n",
    "        unitPop[uu] += tractPop[v]\n",
    "\n",
    "#for i, L in enumerate(CCBlist):\n",
    "#    unitCP.append( CCBcp[i] )\n",
    "#    unitPop.append(CCBpop[i])\n",
    "#    unitGeom.append(CCBgeom[i])\n",
    "#    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "#    borderUnits.append(len(allUnits)-1)  #all clusters are on the border\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined.\")\n",
    "print(\"Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for vv in list(set(vtdUnits).intersection(set(countyTractList[cc]) ) ):\n",
    "                            if countyGeom[c].intersects(vtdGeom[vv]):\n",
    "                                unitNbrs[u].append(allUnits.index(vv))\n",
    "                                unitNbrs[allUnits.index(vv)].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:\n",
    "            for v in countyTractList[c]:\n",
    "                if v in allUnits:  #remember, we didn't add surrounded units to the list; skip them\n",
    "                    u = allUnits.index(v)\n",
    "                    for vv in list( (set(vtdUnits).intersection(set(countyTractList[c])) ).difference(set([v])) ):\n",
    "                        if vtdGeom[v].intersects(vtdGeom[vv]):\n",
    "                            unitNbrs[u].append(allUnits.index(vv) )  #will catch complement later in this county's loop\n",
    "                    for cc in neighborCountyList[c]:\n",
    "                        if cc not in allFusedCounties:\n",
    "                            if cc not in unitCounties:                            \n",
    "                                for vv in list(set(countyTractList[cc]).intersection(set(vtdUnits)) ):\n",
    "                                    if vtdGeom[v].intersects(vtdGeom[vv]):\n",
    "                                        unitNbrs[u].append(allUnits.index(vv) )\n",
    "                                        unitNbrs[allUnits.index(vv)].append(u)\n",
    "            #nLength = [len(unitNbrs[allUnits.index(v)]) for v in countyTractList[c] ]\n",
    "\n",
    "            for v in countyTractList[c]:\n",
    "                if nVTDneighbors[v] == 1:  #surrounded unit. Already handled above\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    surrounder = allUnits.index(vv)  #unitNbrs[u][0]\n",
    "                    print(\"I handled a surrounded vtd\",v,\"surrounded by vtd-unit\",vv,surrounder,\"in county\",c)\n",
    "                    #plotPoly(vtdGeom[v])\n",
    "                    #plotPoly(vtdGeom[vv])\n",
    "                    #plotCenter(uu,vtdGeom[vv])\n",
    "                    #plotCenter(u,vtdGeom[v],6)\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(surrounder)\n",
    "                    #unitPop[surrounder] += unitPop[u]  #already taken care of in a previous loop\n",
    "                    #unitPop[u] = 0\n",
    "                    unitGeom[surrounder] = unitGeom[surrounder].union(vtdGeom[v])\n",
    "                    unitCP[surrounder] = unitGeom[surrounder].centroid\n",
    "                    #del unitNbrs[surrounder][unitNbrs[surrounder].index(u)]\n",
    "                    #unitNbrs[u] = list()\n",
    "                    #unitCP[u] = Point(-888, -888)\n",
    "                    #unitGeom[u] = unitCP[u].buffer(0.0001)\n",
    "                else:\n",
    "                    u = allUnits.index(v)\n",
    "                    countyUnitList[c].append(u)\n",
    "                    if v in borderVTDs:\n",
    "                        borderUnits.append(u)                    \n",
    "                    for i,geo in enumerate(CCBgeom):\n",
    "                        if geo.intersects(vtdGeom[v]):\n",
    "                            unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                            unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "            #if np.min(nLength) == 1:  #at least one surround in this county\n",
    "            #    plotPoly(countyGeom[c])\n",
    "            #    plt.show()\n",
    "\n",
    "#CCBunits = CCBlist.copy()                        \n",
    "#for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "#    for ii in range(i+1,len(CCBgeom) ) :\n",
    "#        if geo.intersects(CCBgeom[ii]):\n",
    "#            unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "#            unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"Whew, we now have a set of\",nUnits,\" units (vtds,counties, clusters) and their neighbors to map onto polygonal Home Districts\")\n",
    "print(\"We resolved\",len(surroundedVTDs),\"VTDs that were surrounded by another VTD\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "0ef0d7b5-059a-46ac-bd3f-5edff09c2aeb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now (still CO special) - convert the vtd lists to a unit list to account for surrounds\n",
      "working on converting HD 0 from vtd list to unit list\n",
      "working on converting HD 500 from vtd list to unit list\n",
      "working on converting HD 1000 from vtd list to unit list\n",
      "working on converting HD 1500 from vtd list to unit list\n",
      "working on converting HD 2000 from vtd list to unit list\n",
      "working on converting HD 2500 from vtd list to unit list\n",
      "working on converting HD 3000 from vtd list to unit list\n",
      "orig unit avg and sd usage are 0.9996 0.21908\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now (still CO special) - convert the vtd lists to a unit list to account for surrounds\")\n",
    "HDunitList = [list() for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if t%500 == 0:\n",
    "        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "    for v in HDtractList[t]: #inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "        if v in allUnits:\n",
    "            HDunitList[t].append(allUnits.index(v))\n",
    "    for c in unitCounties:\n",
    "        if countyTractList[c][0] in HDtractList[t]: #inVTDlist[t]:\n",
    "            u = allUnits.index(c+0.5)\n",
    "            HDunitList[t].append(u)\n",
    "#    for j, L in enumerate(CCBlist):\n",
    "#        c = L[0]\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(j+0.25)\n",
    "#            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "afdf3e75-821f-425c-8a41-cb2e7f971dbd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3103 3103 3103 3103\n"
     ]
    }
   ],
   "source": [
    "print(len(unitGeom),len(unitPop), len(unitCP), len(unitNbrs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "2f427574-f09c-4145-95d4-ae364974c4b9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3103\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(nUnits)\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.8:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(\"u\",unitGeom[u])\n",
    "    if unitUse[u] > 1.3:\n",
    "        plotPoly(unitGeom[u],0.3)\n",
    "plotPoly(MAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0cdd7944-5fd3-481e-b803-f9359dd024f3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 0.61239 0.17788\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "unitUse = [0. for u in range(nUnits)]   #2/14/24 -- jumping in here with 4 CCB's\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "beb8908f-1855-4224-9cbe-6f484a193f5a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "af8a4945-40c2-40df-8dd4-d516f4de2f0f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0\n",
      "working on HD 100\n",
      "working on HD 200\n",
      "working on HD 300\n",
      "working on HD 400\n",
      "working on HD 500\n",
      "working on HD 600\n",
      "working on HD 700\n",
      "working on HD 800\n",
      "working on HD 900\n",
      "working on HD 1000\n",
      "working on HD 1100\n",
      "working on HD 1200\n",
      "working on HD 1300\n",
      "working on HD 1400\n",
      "working on HD 1500\n",
      "working on HD 1600\n",
      "working on HD 1700\n",
      "working on HD 1800\n",
      "working on HD 1900\n",
      "working on HD 2000\n",
      "working on HD 2100\n",
      "working on HD 2200\n",
      "working on HD 2300\n",
      "working on HD 2400\n",
      "working on HD 2500\n",
      "working on HD 2600\n",
      "working on HD 2700\n",
      "working on HD 2800\n",
      "working on HD 2900\n",
      "working on HD 3000\n",
      "working on HD 3100\n",
      "out of 3097 total HDs, there were 2586.0 contiguous and 2957.0 complement-contiguous HDs\n",
      "21 HDs had both discontiguity problems, while enclave-only = 119 and discontig only= 490\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 511 119\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE - continue here for option 1 or option 2 drawing method\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "for t in popHDlist:\n",
    "    if t%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "40f06e44-45be-4a36-b62c-26698af70e06",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 685628 district pop vs 721714 target\n",
      "we'll also trim any HD with total islands' pop <= 14434\n",
      "working on HD 51\n",
      "working on HD 915\n",
      "working on HD 1429\n",
      "working on HD 1919\n",
      "working on HD 2541\n",
      "working on HD 3043\n",
      "Out of 511 discontig HDs 511 had discontig HDs.\n",
      "Of these, 482 won't be under 685628 after all minor discontigys were shed, while 29 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "There are 29 HDs still with both discontinuity problems\n",
      "Additionally, 18 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for t in sPgenerator:    \n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4037f8cb-661b-4032-bfb9-e147975e3bbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/13/24 - classify further: ID those with adjoiners intersecting the map boundary vs internal islands\n",
      "Out of 137 HDpolys that generated enclaves, 0 had contiguous adjrs, while 101 neighbored a state boundary while 36 had only internal enclaves\n",
      "working on enclavy internal number 0\n",
      "Here are the total enclave pops for enclaving HDs not touching the state boundary vs. the original HD pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"1/13/24 - classify further: ID those with adjoiners intersecting the map boundary vs internal islands\")\n",
    "internals, edgers, nOK = list(), list(), 0\n",
    "for t in eLgenerator:\n",
    "    twoNbrs = get2nbrs(HDunitList[t],unitNbrs)\n",
    "    isContig, adjSublist = isContiguous(twoNbrs,unitNbrs)\n",
    "    if isContig:\n",
    "        nOK +=1\n",
    "    else:\n",
    "        if len (set(getAdjoiners(HDunitList[t],unitNbrs)).intersection(set(borderUnits)))  > 0:\n",
    "            edgers.append(t)\n",
    "        else:\n",
    "            internals.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDpolys that generated enclaves,\",nOK,\"had contiguous adjrs, while\",len(edgers),\n",
    "      \"neighbored a state boundary while\",len(internals),\"had only internal enclaves\")\n",
    "    \n",
    "for i,t in enumerate(internals):\n",
    "    if i%200 == 0:\n",
    "        print(\"working on enclavy internal number\",i)\n",
    "    fullEnclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    tEpop = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in fullEnclaveLists ] ) \n",
    "    plt.scatter(HDvPop[t],tEpop)\n",
    "plt.plot([aDP,aDP],[0,5000],ls=\"--\")\n",
    "print(\"Here are the total enclave pops for enclaving HDs not touching the state boundary vs. the original HD pop\")\n",
    "plt.show()    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "05f929ce-4f94-47a6-baf4-60c5a89e2ae5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 757799 district pop vs 721714 target\n",
      "working on enclave-y HD 358 . We have evaluated 0 of 137 enclavy HDs\n",
      "working on enclave-y HD 183 . We have evaluated 50 of 137 enclavy HDs\n",
      "working on enclave-y HD 1733 . We have evaluated 100 of 137 enclavy HDs\n",
      "Out of 137 HDs with enclaves 137 had enclaves.\n",
      "Of these, 130 wouldn't be over 757799 if all enclaves filled, while 7 were too populous\n",
      "here is enclave pop by original pop for those we can fill\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "for iii, t in enumerate(internals + edgers):\n",
    "    if iii%50 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by original pop for those we can fill\")\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "8987ad1f-d372-415d-a2ec-8fc6736c5102",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "36 101 21 11\n",
      "7 7 130\n"
     ]
    }
   ],
   "source": [
    "print(len(internals),len(edgers),len(doubleTroubleList),len(set(edgers).intersection(set(doubleTroubleList))))\n",
    "print(len(set(edgers).difference(set(canFill))) ,len(cantFill) , len(canFill))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8fa887be-92e6-422a-8e80-e00fd3265aab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 0.6157 0.18013\n",
      "CCB cluster 0 = unit 2820 with pop 44650.0 now has use of 1.0542210879999991\n",
      "CCB cluster 1 = unit 2821 with pop 65547.0 now has use of 1.0179936399999994\n",
      "CCB cluster 2 = unit 2822 with pop 105949.0 now has use of 0.9093165280000003\n",
      "CCB cluster 3 = unit 2823 with pop 42401.0 now has use of 0.9883110639999999\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "bd070993-e933-47b2-a104-04d4044bdce4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcenter distance for HD 0\n",
      "working on avg unit-to-HDcenter distance for HD 800\n",
      "working on avg unit-to-HDcenter distance for HD 1600\n",
      "working on avg unit-to-HDcenter distance for HD 2400\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([2822, 2823 ] ) # { 4176, 4178 }  #fill in based on above underused cluster units\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcenter distance for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "b759b3c7-b8a3-4d2c-a8fe-50fa93b3e940",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "#HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "6e2e44bd-a084-42f6-b533-5dc6d21912a9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this code will solve large enclaves so HD and complement are contiguous for 7 HDs\n",
      "working on HD 180 cantFill 0 of 7 .Time is now 0\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 0.61563 0.17995\n",
      "CCB cluster 0 = unit 2820 with pop 44650.0 now has use of 1.044757511999999\n",
      "CCB cluster 1 = unit 2821 with pop 65547.0 now has use of 1.0179936399999994\n",
      "CCB cluster 2 = unit 2822 with pop 105949.0 now has use of 0.9093165280000003\n",
      "CCB cluster 3 = unit 2823 with pop 42401.0 now has use of 0.9883110639999999\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug = False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %10 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for eL in enclaveLists.copy():\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border enclaves\" )\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find oop end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debug:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debug:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "f58fe2d0-3c62-412f-8984-ff5d67ea9b10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After above work, re-classification of contiguity problems?\n",
      "working on HD 0\n",
      "working on HD 100\n",
      "working on HD 200\n",
      "working on HD 300\n",
      "working on HD 400\n",
      "working on HD 500\n",
      "working on HD 600\n",
      "working on HD 700\n",
      "working on HD 800\n",
      "working on HD 900\n",
      "working on HD 1000\n",
      "working on HD 1100\n",
      "working on HD 1200\n",
      "working on HD 1300\n",
      "working on HD 1400\n",
      "working on HD 1500\n",
      "working on HD 1600\n",
      "working on HD 1700\n",
      "working on HD 1800\n",
      "working on HD 1900\n",
      "working on HD 2000\n",
      "working on HD 2100\n",
      "working on HD 2200\n",
      "working on HD 2300\n",
      "working on HD 2400\n",
      "working on HD 2500\n",
      "working on HD 2600\n",
      "working on HD 2700\n",
      "working on HD 2800\n",
      "working on HD 2900\n",
      "working on HD 3000\n",
      "working on HD 3100\n",
      "out of 3097 total HDs, there were 3068 26 0 3 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"After above work, re-classification of contiguity problems?\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "\n",
    "#40 5 25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "45e3c17c-8c16-4bc5-b7fc-25b9250ed11a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we will regrow all disco'd HDs off by more than  36086 but less than 180428\n",
      "... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\n",
      "This is a total of 29 HDs to triage in this block\n",
      "working on swell-filling discontig HD 159 our 1 th HD we think we can swell out of 29\n",
      "working on swell-filling discontig HD 1097 our 11 th HD we think we can swell out of 29\n",
      "working on swell-filling discontig HD 2222 our 21 th HD we think we can swell out of 29\n",
      "we partially regrew 2 HDs, leaving 27 to regrow from scratch\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE CANSWELL CODE\n",
    "print(\"Here, we will regrow all disco'd HDs off by more than \",int(aDP-minPostFixPop),\"but less than\",int(0.25*aDP) )\n",
    "print(\"... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\")\n",
    "HDnAddedUnits = [0 for t in range(nHDs)]\n",
    "maxGap = 0.9 * np.median(unitPop)  #set a reasonable gap prior to picking the last block\n",
    "HDdiam = [HDpoly[t].area ** 0.5 for t in range(nHDs) ] #in case not defined before\n",
    "badDiscoList = list()\n",
    "nCanSwell = 0\n",
    "triageList = discontigOnly + bothProblems\n",
    "print(\"This is a total of\",len(triageList),\"HDs to triage in this block\")\n",
    " \n",
    "for i,t in enumerate(triageList): #canSwell\n",
    "    if i%10 == 0:\n",
    "        print(\"working on swell-filling discontig HD\",t,\"our\",i+1,\"th HD we think we can swell out of\",len(triageList) )\n",
    "    distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "    starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    if contigPop < 0.75 * aDP or contigPop > 2.*aDP - minPostFixPop:  \n",
    "        badDiscoList.append(t)\n",
    "    else: #rebuild from this big piece\n",
    "        nCanSwell +=1\n",
    "        gap = aDP - contigPop\n",
    "        origGap = gap\n",
    "        currList, addedList = contigUs.copy(), list()\n",
    "        adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "        nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "        nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "        stillGoing = True\n",
    "\n",
    "        while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "            while i < len(nearHDscore) and notYetPicked:        \n",
    "                listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "                if canAdd:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't add any more units without creating an enclave\n",
    "            else: #we selected the best unit to add legally\n",
    "                gap -= unitPop[unitNoToAdd]\n",
    "                addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "                currList.append( unitNoToAdd)\n",
    "                for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                    if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "                del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                for i, uu in enumerate(nearHDlist.copy()):\n",
    "                    if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                        del nearHDscore[nearHDlist.index(uu)]\n",
    "                        del nearHDlist[ nearHDlist.index(uu)]\n",
    "        for u in addedList:\n",
    "            unitUse[u] += HDweight[t] * nDistricts\n",
    "        for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "            unitUse[u] -= HDweight[t] * nDistricts       \n",
    "        HDunitList[t] = contigUs + addedList\n",
    "        HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "        HDnAddedUnits[t] = len(addedList)\n",
    "    \n",
    "badDiscoList += enclaveOnly\n",
    "print(\"we partially regrew\",nCanSwell,\"HDs, leaving\",len(badDiscoList),\"to regrow from scratch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "f57325dd-523c-466a-80cb-8e10b739b4ac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous avg use and its sd are 0.61563 0.17995\n",
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 0.61564 0.17991\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"previous avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "2e54bac4-c327-473d-bbb4-257486bddd20",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes about 5sec per HD :-( The total number of HDs to fix is 27\n",
      "swell-generating HD 353 our 1 th HD we must regrow out of 27 0 sec elapsed\n",
      "swell-generating HD 1153 our 11 th HD we must regrow out of 27 12 sec elapsed\n",
      "swell-generating HD 2816 our 21 th HD we must regrow out of 27 34 sec elapsed\n"
     ]
    }
   ],
   "source": [
    "#THIS IS THE MUSTSPAWN code block\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes about 5sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    if i%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDvtdList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "b78199da-ac7c-4cfb-ac0b-26363a8a8c56",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prev avg use and its sd are 0.61564 0.17991\n",
      "defining and displaying current unit use after most recent manipulations; compare to original farther above.\n",
      "current avg use and its sd are 0.61986 0.17504\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"prev avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after most recent manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "a2242181-3a07-40b7-ae56-bbe47bd2dc79",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final check -- any more disco's ?\n",
      "working on HD 0\n",
      "working on HD 300\n",
      "working on HD 600\n",
      "working on HD 900\n",
      "working on HD 1200\n",
      "working on HD 1500\n",
      "working on HD 1800\n",
      "working on HD 2100\n",
      "working on HD 2400\n",
      "working on HD 2700\n",
      "working on HD 3000\n",
      "out of 3097 total HDs, there were 3097 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "print(\"final check -- any more disco's ?\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "979cba74-de28-4157-be12-db1ffd98fc38",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "625 still has an enclave\n",
      "625 was also in the triage list\n",
      "the total and enclave pops for 625 are 728354 45591\n"
     ]
    },
    {
     "data": {
      "image/png": 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mDbBTJ4giSNbGv8j+S1gzS3CPavyoDQCdVSZb3zTCfWuCq7cDQTHuqPWlcxy1Xkmf2yN56Ou+DJ7SgtTz+Ux/eGON+jbl57HlkznoHBTc9P5dBA66WmvFajGzPuMQtwz+sso+VDHObJ25hMKS6pcWl4wm4lq0QDKZq9e+uBiHnoOr3X9N+PaTO7AKoNaXRsIoFEo6xfZh9pQVTOx6Hztb5iBh+yRka3Y+7Z0c+DAygFfCrp94zY4dW7ArHzcwgihgtdotH7YgWAR0HnWXmbSmnF18FoCgu21P7d7UEQSBgEg3lGqRln1qlhH14O8r8Ax0oOXdExCusZwUFmXy+fyxjPbuUmZ7RXQfPBj/mDC2f7WI86lnqzWuqFEjOLgT17Y9krVqh1XJbCV/xQq8nqmfjM+JcfvZ1a8L0WvOEHnoQIVtukb3RXQNQVGDpaWRXi60cdTz2plk3jibVFtx7TQ1GjnW1q583MCICsFu+bARoZGdsP6h6GAaBWEuOAc17UiX2iCKAjE9bVM+zIUFnJo7n8RzJUSPH42gKPsImzynP/5Owdw8+Itq9deyTxdajupBwu/72fTRHPZu2YxUhcIuWa24TpoCVjPnRkxEMpkqbZs9ezW6li1Q+3pU7+RsIOnkPvJHTUT9yhP0XbUblbqqBG8yQg3eNApB4JkQH4qsEj8mZrA/r/oWIjt2rodd+biBKVU+7JaP6iJZpSYRmmwuseBcZCb0tsjGFqVeCe/gzY75Z2w6ZsXbC7BYBIY+PxJRrS6330/pwIieLyOK1c9B4dM8mF5P3ULr+waQnZjGtg/nsWHJEgoycq7kY5HMVvI37yfh3qcpOXKYyP0HcL5pDOfHTKZgW3mrgyzLZM38Ec+nHrDp/KqLVmsg11FB277jq6Uw11SpFoANHUuvw2H7ThNXWFKjfuzY+Td2h9MbGFEhYDU3hdfpfwNjTj4oG//7EgCTfGP663z94Ho8gxxp0dufrqNDmfHsVkoKzWgdru/bkrb/II76EmIm3FlpG2+dJ2mXDhISPqTSNpXh4uLOwAnjsJjMbF+7hk1/LsahRIMuLwen1bNwaN8bx8GDcRndB1GnxfOh8TgO6EbKy++SNdMZn9efRB1QGsVjTkpHdHRE7VP3Vg+LxczmX99Hblv/RfwEQSDaoONcr1a03HaU3rtP0sfVkS4uDoTqtXRw0uOnLa8E2mn6NLaN16583MCIChGzsXqOcXYgPzENsRovwfpGqVViVolcmHGUqCfbN7Y4dUZhrhG1VkF0d1+2LzhD3M4UzCVWDq9PoNPI0CqP3fXlr+RlW+kxeUCV7WK927Hl2B81Uj7+QalW0WtYaVIvWZa5kHSM06fmMOibt8u11TYPJGTOdHKWbiD+/qnoO3dH1GrJX7sS7+efrbEMVbFr8lg8s3LpvrT+Imj+jV4hcrZXK7Zm5/PGmWTeP38JgFfD/Hg4qO7Cpu00DE0g2MWufNzIKBQCUt0ncbxhKUzJROHcNPIYaDr6YDmQ1thi1BmSVeKvd/fQcWQoLXsHENzSgzN7UmkzMJjgGLfrHp+SIHPT25MQ1ZUrh6aiLJac+5uHW9xXZ3ILgoC3gzen8wqqbOcysi9OQ3uR8c2f5C78i5Clc1Aa6qcistvuM/huXt0o/klFVokjBcW8FOrL/4K8moyPlJ3/HnafjxsYUSHak4zZgCiLWPKbxpp28IgQtCUWrKYbQ3tc8d1RfEKdadO/NIeKk5uWdoODCWnlgViNlOwKUSLr4O4q2wxeMJR+gX1p275uo0vO//g1gecLWHZbb07vW1dpO1GpwGvqJJpvWFJviseZnasp0IuYzI1znQZeXmK5N8DTrnjYqRV25eMGRqESb0i/gfrCwd8Da2HTWKbKOJSBKAgo1P/94l07Fp0lK7mAwffbXhzParSw/7tZOHuo8OjUvcq2P3R5g/UJG8jNja+pqBUS+8zrRJ44hrZvL47P/LxO+7aFpa/exckPXiNo4Ty8/JvbcGTdKQnBOg3+GlWdvzjyszIozs+zF8JsSOzp1e3UF0qVwr7sYgNqFz3K4sZ/2WefzcU89xS5GiUBjS1MLTCbrKz89gjZqUXc9nInmzKZmgvyiVuwgjPHiolpo6Lt/ROue0x4+BCesJQwYe4gRjtFMeXWRbWQviyiICKv2ULHj76qsz5tIS87FceNB+m1YX+5yrcNiVKAXm6O7M0rpIerbZlhK0OSrMx980UAAmNa0W/ygyiU9lfTjY7d8nEDo1AruE4eJDvX4BTkg6hUcG7J9kaTIeNEFoU/HCbPoCL65c6NJkddkHA8i/jjWVjNEit/OMr2BWc4uDb+uonvzHnZrHxnHmq9huEv3UTEhNuvmzDsH2KiRvN86/9x3JxDiamoLk7jCpLJiN6z4Yrl/UNuTiob352KeVivRlU8AF4+nURCsYmuLgZK6iiMf8sfv9B64HDu/PBrDq9bSc6llDrp107Txq583MCoVApke5qPalOSk4dkseLdtXHya8iyTPbMo+SrRGJe7oKo+m/fnqFtPHnk237c9mongmPdKM43cWh9AjOe3lrlcVs+n0+7YRFEjBuFysnV5nF7dfwf4/z7cN+fvUlM3ltT8cuhHjWMHS89WGf9VZdtk8fg06EH/Z9tvCWffxjr7Uqqycydh88z+eh5fkhIr3FfsiSxZ+kClCoV7YeP4uCqv4no3B33gKZRW+lGpiksb/23n252qkSpViLZlY9qI1tlZFkiccF+JEvjmIx0ooBD7//yYkt5dAY1rfsH0f+uGLybOeHXvOL09ZKxmE3vzUStEfHvWbV/x/Xo0ed1nu7+Oo+vnsLBAz/Vqq9/6HPvK4gXk1n+0p2YSurWqlIRBbmZLJ7QC8HRQKfxj9a4AF9d0sXFwJbO0cxqHcqsVqHszi3k4eMXWZyWXe0+zCUlHFi5lHnvvIJCqaLbrZMAcPH2pTA3mwuH9hO3YyvxRw/X12nYwZ7nw049otKqkKyNfYn9d9C5OxP91k0c/WIpZ+ZsJmJi3wYdXxAEcgId0a25iNQnsFpRIP8lts49zdn96WgNKr6bugmdowqPAAOdbgqhJN/EidmLCWrpSeTNI+tkvDbhw/ncwY/nV07mu6ib0etcat/n5z9xbNFMVj0yhhE/rqxRxEf+pn0ofT0RVUqQJVQBPojqso/igosXWfm/0TiMHEW3Wx7DZDGhVlaczOtswikECxSbijh68SB92w3Gy6N0eejQsT2Yi3NKo97Eun0WCILADy2akWW28O7ZFI7kF3NfgCc+morDoUsKC9g5/08unT1Nm0HDGfvCG2V8O8I7dsE9IJA9S+ZzZP1q3PwDueeT6Vf2m0osHFqXQLvBwShusHvj/yOC3BTsL9eQl5eHs7Mzubm5ODnduHUtGoIjGy6yec5ZHv6mL0IdP3huZC7tP0nW6tPEPF83L0FbkGWZpBe2YpZlXB9ohUuoS4PL0BBYjFbys0s4tSeVE9uSUWKkj/AyCq/m+D7xa52OtWX7NPan7uexMXPqrM/lD92E192T6dB5tE3HmTNyONOjK7pOQ0CWQJax5mSBzNXoA1nC6KDhm44JuAa1pcCcj9FixIQF8fJ8Nc+aTytdLD4uvuxM24Wf3heNoKG5e3PmXJjLC11f5I99v2PESJJ+JLNHDkddz8t427ML+PjCJcb7unGrz9XcLcX5eXxz3+24BwTRddzthHfsjEJZdTK/w2tXcnDV32SmKNE59+KWFwcx+63dhHfwoqTATP+7ojG4VlXPxk5VzHlnNz4hzvS+vW6XmG15f9stHzcwGofShFlmkxW11v5TVxevNhGkLD/M8S+WEzN1WIOOLQgCbk+0I+vT/RR8fwSX93s26PgNhVKjwNXHgc4jQ+l8Obtp6poczMdX1/lYPbs9x5xfu7Fn/w+0iLoZnf76Sc2uh9fA4aR9+hmpr4Tg5BuIzu36fWbNXkX6J+/gdv+zeD5xV7llFFmSy0wSqoqrkWWZfWd2cerCcabf/hOKaywn3ZJ7c8+Ku3kx5ll6dx3MpGWHGsTG3s3VwJkiF9Zl5jFEYeHY5nUkx53gwqH9RHXvzfCpz1Srn8KcQrJSdSj1vVDpDSCIzH6rNMfLmb1pRHbxIS+jBAdnDRmJBfz17h5a9wskpqcfbr4O9XmKNxaNPB+1v5FuYP4xTdpzfdiGKIq4dw0jZ/OFRhn/4pxTOAIMCGqU8RsLj76jyNj5NSWZ6WjdPeu07yd6vMmPO99lx4U1TB37V637azXyHqaf3YLHpIkoJ9xJu2erTqVefPwCWT/PJHztchROhgrb2GKdFASBDs270KF5l3L7/PwCWXXvv5KhNdCLJvHCeSJnf88yV1faDB5Op1HjrmvluJZvHv4bWdKjd0zFJ9QZv+Zaet3eB3OJFWOxBbVGybGtSez++xxJcTkExbjRfkgwYe282PznCbpEn8Enyh8COoCqfhK92akb7MrHDcw/D7MmtrLW5Dm3bAdFu1OJerrm9UFqg2NyAYUKgcgBwY0yfmMgFWaT+uc0FGoDgqruU9yHhQ6gR+IWTmeeqHVfjy14jOO5x2kd3ppRX3xF0kefcnrBQrR+vjh6eOAcFlbGF8QYf4nk51/HddKEShWP+qa+s5EWm0x8MnMm2vVLaXb3w4wdWjOL4cPfjODS2QTmf5BG37v6oNXrAdDoRTT6UiWm/ZBmBES6IYjgFXzVtN9rlBeGWTeD4+OwaRr0eBzCq64FZKfxsCsfNzDiZeXDbvmoPpIkUbTtElGvDkOpbZw6LwUKAYNVJmFDPIF9b3zrR87R/VjmP4LVrx++Ty9EqKdcFoO6PMeueSNZueVNhvR8tcb96BV6nmr/FENaDUGWZeSMbLIPHSJ3/XoS8vIQMzNRhYbQ5pNPoKiE+HsewueVF3Hs07EOz8YG6vH2N1oszN64ifgFswjuPYg7/lyCIIpYLVbWzVxA0snjGIvyARmLsYiY3oPpd9foKvtU67SoNAKqKur4eIeU9yfQOKjIdOiBb48noPODsPgRSD0GeneIGgF14HB8o9AU5qN25eMGRlBctnzY67tUH6uErJAbTfEAiHirG2dnHse0NRmuUT6MRhN5WQXoHbU4GPSNJl9dIksShXuXgltbAu9/p17HUqn1vDhmHoNn9yTSt1ONKt8W5GbisGErHfo+BZRaFELGjCFkzJgrbY5uPED8gt/Yf98DRN71AKqAsMZTPIC1DjIWWUZVh2svl4qMzN50AevPpd9DVJubiPSI4OjmfVw6fZ4ze7cR3KoTI594CDdfD0SFyJ+vfoDWoeIw62uJPxaP1WJAEG1TQmWJq067Kh2M/RFOrYDdP4BLMITcmP5TNaWxQxDsyscNjN3yYTuiSoksy+ScTMQlqnHybVw6Go/udDb7TUa2vrj8ynZBFFBrRSxGsJqtqA0CgZEetOvTHDdPl0aRtbaUZKbjeW46+WIQRa8EY757Nc5h9ZfkTatz5a8Rc3hx2V28rnUhMKC8z0RFmEzFbPr6ZaT1W+mXYUVbZIEKnPmPbt7P9i3bUAVHYjp0GPdvfkQVEFLHZ2Eb/YsEFHXwppFlmZ0Xs1m97gLqSyVEtvVm+MyFWK1Gjm3cyald2xFEJe4BAdz+9ps4e15VNOJ2HqYor4CuN/e57jhtBrZn34q5nD94kbB21f/uZFku+0IVRYgaDsU5sOYVaHEzGLzBuwV4x1S7Xzv1g135sGPnX7gNCifht124vNPwyoe5wEjGojjcJ0QwJMgDB4MOpari2zTxXBrH955nwRc7kZFo2y+M9n0i/jvVRmUZ68zR5KtjsWo8MPuPwd2/Wb0P6+0ZyzuDf+ClVfczbdQcPFzDqmx/cu08Lnz1MZpB/ej21zr2DBjM8Ul3IOl1yLJMzNdf4xwUhCzL7Nq6k5tuGYNPIymuFSHIINRinns6vYBNO5JIOpmNo1bJyH5BtI29tqqtio4jB9BxZHn/CmNRMVv+XErcjk30vuPeal+brr5aMhLSbFI+kOSKp/NtJ0LkULi4DSxGmHcPiEpwDgDJCq7BMPzj6o9jp06wKx83MNLl2gv2HB+2URSfCW71f2tYrVYuHY0n58Ql3GL98Izw49jMrajauOHf+voP3YBQLwJCveBWyEjNZsVvuzh/PJlbHmnY5Gg1RhAw6wIxi2q8H/4epb7hlpJ8fNtyT7MRLNr9KfcNrjio9dS25Zz58gPM3q50/OYX/PwiAHC58048O3fGu00bTsyYyblvv6Ptu+9gKizBbDI3KcWjplitEqv2JrNnaxJqCUI7ePHoA21wc65+bo3Nf/zNnsXf0qLf3Uz+5CN0TtWLPjGbzWQmmmg7yNsmmSVZrrxQq94Noi/n7Wk5ruy+151h8LugbLyl1ganCRjD7crHDYzVUloe/r8yEW4qGONyiHyufiNdJKvEiTfWIvmo0TV3I2NBHOlCHLp2HkQMb2tzfx7erkx8YhDfv7CqHqStP1wf/QvT6nlkfTYGpwdmoXX3aLCxu3Z7lpf+6Ipu86tM7PXmle3xx1dw7K13MLq60OHdzwkIbV3muBYPPHDlb58hg0kc/Cm5Dz3I2Q3nKJaMSFYJUdGEMnDacP/vTMnhzTVxxB4upFkBDH8whg5tfGwe8szeOI5v2cB9X/2Osw1LgpIkM/u1v/ENUxIUa1uNlxr5tkkS+Lf//6V4/EMjvxjsyscNjCD847Bl1z5sQZAF1PXk0Jm8+xypm84gBjuglkTC7+iM1lGP1E8CgRrX74g/k8LKmQdo1sb2QmyNjfegcSSlxJG1eTF+Y+5tsHEVaj1/j1tDt/n9Kco6x6C2DzBj+5uErrtAZ/9Ioj76+7p9ODg6YnZyxJiRQcuxXcieX8DMD79DIYjo1FoUKiUalRqNUo0kyWi1Gty8PWgxoH3D1Wq5zjvZapXYkpzDG2vjKCqx8Ez/5tx8hzcrVp1n1ZxTrJp1EkGrwMFDy/jbYvDxvn4ir4Or19J++CibFA+A1d9vwNFdZsTUUTYdB/9yOK0uogjB3SBxb2luEDsNhl35uIGxWiwACE1oEtbUsZot9aKrJR0+T965DMyHsgi6uw25x1KxdNGhdig1Y9dmpvz3r9tIjstl8N1tCW7e8CXf6wIx/QhSIxROczR4cWDiXh78ozf50x/l9gtKNGk6PO6vXn6InPh4TJGReLUttVb1v2s4UBqyXZiTjym3BFOJEaPJhCBCSWEJ54+f4einRxhz/23onBo3amnl+XQe+HEPbt563h4Ww/Bwryv7hg0JZdiQUDJzS1CKAtt2JzPjnV04t3LF18uBsTdFlOtPslpJPJlIypkTDH+s+oqk1WJl4YfLyUkzctd71VM8CnIKSDp5npzUDLJTLqGSrUSW5FV7zCu0v6c0LPemr8Aj3Pbj7dQIu/JxAyNZSyuz/mccEJsAp2dvRBlUs0RQVouVgsxcHD1dKMkq5NyaI0hGK2oPPaa9GWjaexLyYGccvV1wD7ZtPbsytq0+SGZ8Efe9NaRJVD2tKc53fIr5qz6UXJqE1qdhS6orlRp+vHMnpzq2RusFgav3Iyir92gUZblUYf33dlHE0c0Z3MqHlkZ2acHC7+dwavtRWg/pVGv5r0sFt3+x2cqTa0+walciq57sRZR75de8+2U/jyF9gzm0NRmyTKTszUYaEV7mmkuKi2fpp5+id3YntldfdA7V9w/JSS8g9aIDfSeFoNJePyPq1jmrOLJ+BW7+YegcHdEaDFgKU7GaMqo95tUTDIMRn8HOb2DEJ0DpsqggCjfws7PxnT7syscNzY1649Qf1uMFRL023ObjzEVGTny8CVknglFCQkLf3hudiwNFibm4j43Av1XdhVyePZbAuj+OoNYruOWx3v9pxQNA7+1L1q1/kv/DHZjHvItji24NLkPEnkPkfPYMqVOG4zOjer4zyes3oIu0LTT4zO4T5GZm49G+I5t/WUlc0lncXdwYcfdY1Pr69z04nVXIwA820rGtD2uf6EWoc/WsL6Io8sJr3QH47LM9fPz4JnpNjqbzZZ+Q5V99x5CHHqJZ6/IWkevh7utMaCsTaRfTielRdVtjUTEHVy1kyjefo74mH0/RpfNk/bLY5rEB0s8ks+tAb7h4CFmSSy2RsozVIhEQ5Ubzjt44ut1ghezstV3s1Bf/hNfZl12qj6yUUVRj5gVwctFeCk9nonBUI6aZMfQNILRnw+QP2LToMK36NKPLwNgGGa8hcGvZjgKPPzF9Pxpz+NZqzYDrGpfHPyT9qVtJe/xWvD67fg2Y5nfewaFbbiWhfz807u4otVrcgqrOSmssKsEkmdm8bTPRrVtw9+39Ob3lKL98/iNDhw8joA6V1H+TWmhk4Acb6dbRjz9utt2x+R8ef7wj23cns352HLJVxsWUjsZBVyPF4x9EpZLrBebt+XsbuxfPpt3wW8ooHlBBng8bMBpF/H0KaXt/WediySqRGJfNry9u5/bXO+PqYy9cV1fYlY8bGPmy1nHjmg7rlvSDZ0B9VVPLScsicWMcliITOn9nDJ7O5MVnUpKYi5BtQdYriL6nG7mJmbhH+ZZ7GNYnw+/qwpLvd3F4w0WgNJzayUvLgNva4u7lAsChnXHsW30OS8lVE6vOUU10V3869IluMFltweDrS4JLO1QnNqFq2zh1OTze+5nkCX0oXPEnDkMnVNlW5+JC8EsvkvDzLwgmI4YdO3HYuweNofJljNg+bYntU/bFH9OvLSqtmu3rtnBrPSkfSYUldH9rHU5+DrVSPP6hWyc/PD31zPvyAKq8bQy+x3aL4bXonJQc2ShhlTbQd9LVcPHslEw2/7mUzMQLiAqBez56D71z3dbIST95HqfA8lE9okIkKMadO97uyr4VFyjINqJxUCGI4Oyho8PwEKwWiTN708jLLL5SodnO9bErHzcwdqWj+uReSCF99jECHu6E1Wzl2I9bIMeMvrUnmkB3Ci5mk37uIlofA/59I3EP87lSxlzv4djg8noHuHP/m1eLd5UUGzm6+ywLvtjB/W8PZf+Wk+xffZ4h97QvzQVCqRPkqSMX2TznBB5+zjSL8GtwuauD05hXKfn1djRhHVE7XT8dd10jqPX4freAxDtGIeo06PqMrbK9b58++PbpA8DOyZM5O3cuMffcY9OYF/afYuOmjdx89201FbtKfj6axNt/HuL2UZG817XunCqbh7jw/Md9ePPhBUR3amnz8ZIkcWnXcTKXnSKwZzCH5UyiurYASi0Zh9buYttfs2g9cDidbuqPb3jl/kCyJNV4KaGwSEWwv1ul+508dPS9IxpZljGXWJFlmf2r4ln6xUEUSpGwdl6knMmp2eCNgL22i516xVJiKv1DgOKjR7EWFuLQqZNdKakAtbMBSbKStPoMUvJRxJaOtHioz9UGXRtNtGqh1Wno0DuGvcsvcnTXOfavuUDnm8KuKB5QumYf1TqEgpxi1s06zL1vNE3lwznIl4y+z5P19US8n12COT+H1PObyczaQ6s+ryMq6n85RvQIwPO5l8mf/+t1lY9rUfnXLMHYhRPn0Kk05F7KZOPC1TQLDqbd8Lrze/lh0zkGdgqoU8XjHwRBQDAXs2LZGgYM6o3uOsnijIWFXFyxG+OhbARZQHYW0Xf3RV6bhYfuEoun5WGx7EdQ5OHqG8L4117BI8Cryj4BZOQaZ3I1lVhQu1SufPyDIAiodaWvzS6jQinIMeLopkWWZeJ2pmC1SiiaUo6XKmjst4Bd+bhB2fLWXI4kOKOyFHO6UweUllJFxPv113G7bXwjS9d0yM/NYeUvP5Fy8hgeej/aNxtLyKTOqLXqxhatRoR39ODY3nNEd/Ujtn35F83Wvw9xdFsiXYY3bwTpqo9H98GkHFpKxnv9UEqFpOS3orBtOie/iMVs8MTi15Y2Qz5FUY+KiLbHCNI/sK3YneXQIcRWrWweq8/EIRxdu4+juw7h4exGemq6zX1URWpqAR16NKvTPq9l/AuvsXLFOt5/9qVSBUAAtYsHI28fT8vo0vT1BckZJP26FynPjDLMQPgTA9G5XbUaZvifp9NpPfnphZw444wxN5tuA3pXS/EAbA7gkCxmBFGBIIooBROmkvJRS1UhiMIVJ1RBEGje0ZtTuy4R3a1pKvVNDbvycQOy59PFHE5yJ8IlhbZ9vDB3eADH2FgSnnmW1Ndfxwp4/j9VQI7s3M7W+bMRRQW+zSO4sH83LQcMZcxDU1GqGt7Bsa4ZMK7i6qkWs4WtKw5xdEUWd77XGyeXul0zrw98H/6qtPaGILL+zT94/vaJmI25pGWdIXvpoxw78jut2ti2vFFdZFnmbPIutM4GjLtWoek8uFrHWVVKDD62ZwQFaDGgPS0GtOfC/lOcOnQSs9nK+eQ8tCoRX08DKpWi1KnSRsvlhqwCVBaZya3qL+17ZFggkf+7+8pns8XKkaMnmff5Jzi99BLWwxcwb81GO9iHgG6tUKjL32serULwuOzv0ppBFKVns/ajL4nbsJm+Tz+I2uE6UTly1csuJQW5JM24i7CsDcS798Qt+zB5ah+M3m3QewzClHIBomvuCxXV1ZelXx4ksrNP08pw20SxKx/VJCUjHW83dwC27t/HkQPnyU8yX9G2lU4gW8DFT8fdE25CpVRitVpRKEqzjOYW5LNk1UYkq4x/gAfOTo5Eh4Zi0Net93TavlPsO6Yi2CGZgR9Murx1IABRW7dwrG9fcpYv+3+lfFgsZhZ//w3JJ46id3Jm1COPYzFbOHVgH3e++SEuHnWT0vvI3lNcSkpDRqb0f5f/lQFZRgYcHR3oMahhMyluWLifuB2X8IkwMOLJ6P+E4nGFy2XVC82FAKg0zvj7ticvchhF8TugnpSPrOxz3Lb+IYb00DHxrscJ/mEa+p43VXnM+XXrEM0W/LpXf7mkxGzBbLWALHM2NZ3kvHwK45MRUwtJfWU7l5rpydeIiHEF5KsFVBYZbWnJJs45KwjNtbLPR41HsZU8gxIh2AnBKiNezAextKicS2Y+a17sj7oBX4gqpYJ2bWIpGHYHiq/PUuCcTfOXBqE2VD9cVe/pyk3TXuXk4vXMfep5uk+4g2a9K1auATAV4Fe4r8JdSdtmo9j8AQ5dHsLSfTZOaRdROXvg5+jOuR/uIuv4MVqNnWLraZZBoRSJ7eHPsq8Po3fR0HlkCAbXGyw8tw6xKx/XYePu3exafRpDoi/5TukgCzjme2BWOIJXFoISkMFySYVjvgem8/Dx+Tkgg0OKNwXuaTiHKik6pEFrckBGpoASoIR1zse446k++HvVbKb0bywlRpZ9cxgN0LeC2iSCWo2Qm4da70DK119TnJCA6OqC+6BBOLZtVycyNEX2rl9LdkoSUz74Ao3uanGroOY1DwusiNUr1tIitgUIpcmJrv4HUPr3jp3bG1T5MBpNxO28xOS3B6KuYLb5X6HEWlzmc2FBCg5nN1KQfwmDY93cP9ei0TjSX+nGLe3HsmvQr6S8/RYl3l/iMLA/ap0Bz4hWhMR0RRREBIUCU0kRGa+9xpYe7dmx8HOeuPmJCvuVzGbOrV3LnnXryC4s5HyLNggqJaLZjMLLB2cHPZiNeBrcsN7Thl7e5Z2ZjSYLOblG2juoEFQKhigEBCtkZRWRmFKa4TNyUBgGvQokKHltBS6NELYM0K5PWw7v20PX50fW2NcsalQ/grq3Y91HX3Jy9TL6Pfsoamf3cu1klQPJDh2oaNHDfc2jJHr1J7zv/QC4BFzNzRJ057eseGwH/Zw9ayTftTTv6E3zjt5cOJJB3K5LtB/SrNZ91hv2PB9NA0mSyMzLITk9lbSsTNIu5ZB4JBeHRG9wUGOMuoSQqEJ2MBExRkvvjj1R/8tMP33GXKTd7jgm+5LvkoaiYxaaA85Y96ohNI0Bt7Qk1D+QE+fOcOpMPCUrHfjrjX249bZy161Vz6qqwlJUwuZ3FnHhkopilRtj7vDGwa/i2byiVUuKNm6kYMsWZBdnxOwcCn/9nYi1a1D5/jdTc1+P9IR4fJtHlVE86gOFQmTw2F5Vtjly5FC9yvBvfnv2OzBHcHzmOiJu7obW1fCfNAm7a8tezxG9X+ZE1nkMH0civ5KBUMe+H1qtK/mSidZdHqN1l8cASEs8xZGFMyiMO0n2imXE5RcCMoIEKEVSO/ijK7pI4dYiZux9oUx/w2+7DUtODnMXLcJRraFzp87EbdzCbbeMxc3LtpeeRq3E2/Nfj24RfLwN+Hj/y6qlAFdfA42Vg87gpKFYWftMoXoPFwYPCufi6h9Y9Pxeut06iYC+ZSODZFlCkiyk75pHcfo5REBO2INckEoQJgLvnF5h30qNjtAeen54aRUuflrGTOmBtpbJ3hzdtSSfzqlVHzc6/++Vj7yiAn6cuQjxmDsq6doLTo/sVIimWy4PTRx7ZfmkKh6afAvxw5JxNjjibCidseQW5FNiNOJ9TbXO1pHRtI6MJrlzGn/8soaC9b68f+BPRtzbnhbhts/GT/y5mROZXmjJpXcXK37dK088FfHzzxQfOIiuVUtEnQ5rQQFxHTtx6csv8X7oIdSBDZvaurYYS4rZt3ED7n7+KEURZ3d3PHyvzn12rFzGhYN7Gfvk8w0gzfUfsGqVhs/e/fZfx1TuKWeVJNq1bUvf4TUMt9EkM3xUT85vPsXKV5dgtgiEBEHr+weh8a79TK+xcDL44tP9aTi7jdTkPfgE1nFGVEEoF4/oFRBB/0ffL7Pt5N41pB3fR8aKv4ncdpT0HlH0f+1dHJzcES6/8Td/8QVzZv5MgJ8vvXr3od3o0tolpzZuRWoKMY81JDcrncTDG5EBGQHfiI54+AWXaWOxSHUylnH9Atg/j7DXlhNUnMPmT57k1Kbl9HzyU1ROpVaQIquaS8VWXLfPRNm8HxbJikP/5/BoFg0qPZoqFKChk7pgtVpZv2gPM19fh1+kI3pHDbGdQvBrZvt9olCKSNba/bap587g2SwEUbz+u+e/yP9r5cMsmXnzrR8JyW6F3CYd72BXPFxd8HR3Q6/TEOzXx+a01UE+ZY1+1yoi/8bPw4unn5rI3xs2cnypitWfnSZ7ch4929lmlncOcoc9ufg4FtLi7jFVthXVahw6X60noTAYUPboRsGCheQtXIjmjw8IbzvSpvEbk1/feAlHDy9O7dyKLIqU5OdhKS4qdcwTS03i9773Kfoqkj41JA8/Y5uPwu5Nh0i4mFzj8UQFBPZrQ2C/NgBYik0c/Wsni15bh7dTMR2m9McQXnVGzqaCJEll7kdnt3AOugUgLH8C69BP8A/ocsVHpNbIMkbZQlbWGdzcwv+1S+aRdY8grNzE2N0i0vgROPXshfaeWEYOmFDumdFr6lQqsocJgtBg+Rbqw8J+bP0sXOLXkOfXC7LOcibhMB53vFmmjSiCVSFwYm8y0R1qFgViPrIbzeZ7sNyzB1GnRaPzYeDbf3Bh5QzmP3snLXv0IHbSC8iCyF7DTTz4xLM1GkehUDDw5i70GmFi27LDWK1W/v5xD7IEGq2aic/3RlWNpcsts1eyb9kCglp2R5JCa6Q8pMdf4PcXHsfV149Oo28ltnf/Ok2R0BR03v/XyodSUJKvz4Js8AxwZtzQQY0ix4i+fQjwPc62zy6xfVmcTcqHMSuPjbPPoEPJgHfLLt3IssyHH37It99+S0pKChEREbzyyiuMGzeuTLuIH34k/YfvyPj4M45tXUJo62H/CW370LYtWMxmbnuqrFXDarUiimIj5DORkSUZ4Xo5om1AssqIddifUqemzV29aH2HzOnlB1j5yTYM6g10uLMLHu2uroNLksSRn1Zz6Xgq4T1DUTpoObD0FAISIz66lZQ9p5EtVvx7t2yQujKiQqDIWIxBd9VB28UliDZTj3HsyCxS1rxAYU4SwoDXad76jlqPp1SoKEEmKWV/GeVDlmWe2fwMGTnJ3LcLeq/bi1JdQxO9ICA30Fugrq6gvJxMTvz+NArJiFfeKbjpC7q26sbRbUuR17/H3q8uEDZ+Gq6epUu4oigSMDiEi3tqrnxYzx3BGvQ/tMFlrcLNhkzGt/NQ1rz3OHH/G4ERFQq/2mfu1WjU9Bt7+Rl8S+k/q37fy8w31zDmka54+rpWebzOUY+juychrT34/bnHuO2tD1FrbVvyXfHVxwDkZ2Wy9oevWPP9Vzz43a/oHJ1sPp/KqGlOlLrCJuVj+vTpTJ8+nQsXLgAQGxvLq6++ytChQ6+0OXHiBM899xybNm1CkiRiY2P566+/CLpOvYPGQBAEvnrhVb5+bA0py8E61Fqt5ZX64OyFJECBIcmX99+YhVeEnptHDqjUavIP+75fQ77SnTF3+qJxK3thvvzyyyxYsIDp06fTvHlzNm/ezKRJk/D09KR3795l2iqcSzNJ6p3d+fmFm9E7O+Hs7YuLty8GVw+0enfCWg9uMgXM5n/zOennz3LrMy+X29dYvyGULqDU5S0tyRKXLqWyetGWy5EzMoEhfsS0rV2yKEEUiBjRjogR7UjafoJtP+9D/Gkn7W5pjX+fNpz4bR1b96kRJW+Sl6ejkEwMfaQ9B+ceYMGjc3B0FBAVIjvmHCPPqOXub4aj1NVtevmMw2exlJhRatUolAK5RflllI9/iG05EVpOJDc3nswfelMYNhAHQ+2cUM3mEtxENS1jb72ybd+lfTy35Tn8Df587vMoOen/Y/O8z+h3+3O2n1t6Bpr4iw2Skr8u1ZvcjGSQLATeMg2V1gE319LEXFGdBpPqG8ql5e+TmXL+ivIBoFOJmKSaSyEUJiHLFS/faFx9GfHBHJBlCjOSWPPnlzUepyoGT+rAyYMXmP/pDlr296P74DYVtpMkCbVOhyxB28HDcXT3YNG0N7GYTXgGhaDSamnZbzDuAVUvb2sNjvS8/W78mkcRENOCuW+/TNr5cwS3qnjc/yI2KR8BAQG8//77hIeXPvh++eUXRo0axYEDB4iNjeXs2bP06NGDe++9lzfeeANnZ2dOnDiBVtt0w41USiUmdTEOxS588+NcHrn/1kZ5wY4Z1J9tXvs5dTKB/ENKijc5MyN9KY/977Yy8kiSxInzZzl98BieyUaOndHjIGfj171sHYzCwkI++eQT1q9fT9eupf4CoaGhbN26le+++66c8iFbLcgCDLzzfWRZJifzFGnxB8hOSSDt4gly01I4smkeQ+//EJ3D9TMB1ieZ6emc2bOD52bOblQ5KqKujS0xbcLJzy0AuVRhMJssLFmyhLNxrRh5W93UPvHvFo1/t2jSD59n56fL2PDbCXJV3gBIoprI0EK6PV/q3DewfVSZY7PjEljx3gbWvL6Iga+NQqmv+b1elJ7Dzs9WciLTi2iPdE5keBKqSUBQKnDIc6HwUiK4V65UODsHcdo9BG3m6VorH3vO/o1GfVXxn3NyDl8e+JJpvabR3b87xoJcLr39OL4vf8ZulQEPvzBCu5ePMKuIXes2kvH1dAJfeQkXV5dayVld6tRkr9Lj7Vv25alUqfEPjSU1tC+FK17j4MqrEwCLSUNry0gy3jkOgNWsweP+7iiukw1WNlsxrfsLzamPMU/cVrVQgnDl5rOYLOxetoWTcScRBRFZAEeDgbDm4bTq2wGFsmaTk6g2zQhu7sO8r7Zyet8qeo6OwdGgIen4KdLiE8hNTSUz8SJKjZ4Ow0tLH4R36ExYu44UZGeBAPkZ6ayc/inFebmEte9MSWEBMT374RMewabffqQgOwtBFEk4dpjA2JYExJSmmh/8wFRmPD6FCW99hHdo3WepbQxsUj5GjizrC/DOO+8wffp0du7cSWxsLC+99BLDhg3jgw8+uNImNLTpF9rRRZrgIJiOVa+0dH0giiI923UoXXK5Hb78djbqgz58+Ox8lAEmJJOMNV9EmeuAzuQIOJEEKClm0OTypsbjx49TUlLCwIEDy2w3mUy0bVtBUSnJyj8lJQVBwNUjElePsqXCty+Zxo+PTeK+z39B59B4zorunp7oHQyYTSZU6qaVibSul3pc3J3KRNBIkkRAsC/Lli/FeYGVxP1buTK3lcv/a7XBrO/ZKoRWwgGy9xxD7e6MWimXmnHOCZzZ8ENpIwG0sS0I+PgjAFwjA7n95zvZ9Opsjv+5hVb3Dqx8gGuQZRmpuBhRpyM/MZNDs7aScq6A1gOD6dw9moTNx2kVG4hHy34ALH3yFtSWx6rs02QqwCk7AaEOyjhbTYVsNKbS/6/+mCUzOcYc1t2yDk996XWvMTjTdtwDHHR2wvHRNzECnKxc+bBaLPx9xz2gVKIsLKLnzB9wcq47E3p9svfMQeZu3MIo5yIEs7lKy167YZNh2ORK9xv37SZv2SkEfdXLEKZty1GvmYAGMPb+GU3zFpW2zco+z/vLJ2MsAtes3qR//B3RzSK48/H7UGpVSCYr2edS2bN1N5tnr6LvpGGV9nU9dA5a7nhuAEd2nWbH3ydJP7mQkJj2eAQEEhTbkuCWoeidyr5HBFHE8XLAgaObBxPf+QSzsYS89DQKc7I5sXUjG3/7kZZ9BzLogakAFOZkX3FYBnDy9GLglEeZ88YLtB44lP3LFzP11/kolDX0nGgCTh819vmwWq3MnTuXwsJCunbtiiRJLFu2jGeffZbBgwdz4MABQkJCeOGFFxg9enSl/RiNRoxG45XPeXl5NRWpxhTHqZENmdzyeJc6s3pU19+iMh6Zcisbdu9i7zojlkQNstKK4GjBkr+PFkeO4ZyfSKabI51nz8XgU34NUpJKzZTLli3D39+/zD6NprypV7ZeVT4qo9tNzxF/9DCFuWmNqnwARPfuz+yP3uOOF19rVDkaGlEUad0pip1bd7Ph4Hb6BQbQZvToy7O+0pwisihemQmqbbQ6Bn7zNb5p6aBQIEvW0oeUJIEkIUsyckkJCQ88UO646BGt2D5jD2f3/EJ0dz+8O0VBYT7OraPKhfaeXryTQ8tPY84tQLBaUFqK8JETaU8ilg+TSfpMhQhkAVmXlTknKZe7wt/kTvNT3Nuh4myjB9e+QIv8dPRB3SvcX1iUzqkjsylOO0KLPq/j5Fi5D0KXqHHcvu19xo2ZSZBTEAWmAgzq8k7LbQZOYJ3bW/hlyZzctJio3qMq7M9SVIxF70Cvd99Cq9fi6NjwxQiv5cMlv3L6UhZOOh3ju7THaDFjNBdgtZYmPbNaLVgkicOJeZxOt/J45yA6Lr2TA+3ewa1t9Sw812IuzGX7Z/PQlTgRPDQWnKr2mxDcfTENmIW47inUfUYjSdZK/dByci6wxpzO4mGzOTH7EAOfKOv0K6oVuEf50U7bme1/b7JZ9opo2bk5ka0C+PLuzxn26KeoK3imVoVKo8U9IAj3gCCCWrQut9/Bpfz3E9u7Pyu/+ZTmnbqxd+kC8jMzcPGuhYXvv5bn48iRI3Tt2pWSkhIMBgMLFy4kJiaGS5cuUVBQwPvvv8/bb7/NtGnTWLlyJWPHjmXDhg3lzPz/8N577/HGG2/U+kRqg9qowxSYSeh11uFswRZ/i4oQRZH+XbrSv0vZEMsTUaVWjvjRHej+wqcYnCu+iWNiYtBoNMTHx1drvOooHwBR3QeybeFXjHqk4pj5hqLb0BH8sH4q6ZdS8PS5MfOTVEV2fia6khKcPT1x9Paus35FrRZ1UOX3gWQyIRUVcap7j7I7BIEYWcYo6kl1msCZzWfB0ZmCbw8x/JnuODYPIv3AaQ7MPYApMYnmh+egkUtwv/8+wAGIBDEat7vvRlFBYbJjdz7K+NAe/HRkJr8cncPKidPRq8o+8NWn13K+9c04nFiARVDi6B5O8vG5eG6fTpbeFVmpBa9oXDwiSPixN0KLsUT0eR2lquws3GIxkpV7kUEmCHIq9VWrSPH4h/7bj3MiKhq35pWHuOcVFlKiUuPZCOHNgiyx//wxEjIzuJCWxYbTBUiShe/unkhydjqzd+3CUatGrdSiVChQKhQoRDVKUUGrYG9evbkbBXs/oESjos2Ih8vMyKtDVvxJNi+cgc69GbKjI9v2nyBv624kScLP24+uw3rh7H31OSZbLIhzxmF2H0RBz5d4+Jf2JMomNkzag+pfv1V8wjbe3fQsLwYMRqN1R61VVTqBdPf3Iqsgm4Qj5whsWXuLvOqyYl+Yn4da0zC/65N/LkEQRYJbtSU/M712ykcjY7PyERkZycGDB8nJyWH+/PncddddbNq0CRcXFwBGjRrFE0+UZvdr06YN27dv59tvv630BfjCCy/w5JNPXvmcl5dHYAPnmihxz0ad5MreY0fpEFu5ea+62OpvURM6PzsNg3PlacEdHR15+umneeKJJ5AkiR49epCXl8f27dsxGAzcddddZdrLVku1lI9WPe/k9O71/DXtDrxDm9Nj7IsoFA0fNKU3ONJm0DD+eO05Oo4ZT7chwxtchsbE292Xi3IuJWZzg44rqtVEHdhf4T5Jkrgw9mb0R/7CmpOL0tMTY8fBLHllOTq5CMlkxufSTkKUmTjfMwGvx6peRrkW2WxhYqs+PDxkPCP+mMr/ln3CjNFlE3n5TZjHhaN/UnDgFzTGAsw58UhBnTGPnk6r6LIh6CXdn+Hg8kc5+1k09JhKROfHSU7YQtrqF1EWZeOVn4pOXf3SB3l6AfqNZNfzLyMCInC5vhoCYDKZcSkqrHZ/dUl7j70s3O1MkLuBCB9nxndpQ6BnabG3IA9PujSPqfJ4Y9pBhF3fo3rqgs2KB8DGxb/hqFUxYMpDZZYlJavEqa1HWPLrfNQqFV37dMdHToeVLyF3fIPTwUq+2PMxz3d6nrn7viI5cQeenrFkZp8BRJwcfXl81f180fczAsIGkZKUQEhS5UXoFCoFt9x7O3/88Cu3edyOs2/5LKm2IFmtyAplgz7//vn+ZcmKf1TVv1tTx+ZvTa1WX3E47dChA3v27OHzzz/nyy+/RKlUEhNT9guJjo5m69atlfan0WgqXAZoSO58bAALXz7Kpm/PETmtGY762uWEsNnfwgYcF/5G/pg7ODD/B/reX/WSw1tvvYWXlxfvvfce586dw8XFhXbt2vHiiy+WbyxVz/IhiiK3PPMraYmH2bfqJ9b8+iJD7vngusfVB91Hjubg6uUolP/dtOE1Jbx5GBczTrL8xAnOT/kdL28VLu5qBKUClEpiJvZB7diwPkyiKBK6aCEAJefOkfHJp6iSj9LNYKWk0IrHoA54PrSwRn0rZCuSUGp2D3OJIKckt1wbL69YvPq9Xa3+tGoHuoyeQV7ORc7MGsXp7V+T7+KPa4+nCY0ew95l/0MuSCWsmvJpZ3zNm2tO8rDu6jKXhIx8OZeHSqvFa+oj1eytbmkTeIHJHV9Ho7a9hlHe4emw+SMUY2egqML6UxUZBWZiOrYu5w8lKkSiercmqndrUs8ks2PVJkanP0hizEOsMq3i5MFEPhj9F64uIRjNhXy/+0OKTQW4qhxYUZxIG9GByWFjCAgrTZFgVUhc8sqlWRWyOHo6M3zMSJb+tpCJz9xbKx8tQRRRGpxIOHWS2M41TAJYA2RJIuXMaYrz8ipcnqk2/7Vll38jyzJGoxG1Wk3Hjh2Ji4srs//UqVMEBwdXcnTTwM/Di07/82TbNya+/nAxT700HlVNHXmw3d/CFgKiO7A8ygXDrMVwHeVDEASmTp3K1KlTr9uvbLXYlJ/CK6AVLXuNZ9X37/PLy+MY+eg03Lyr+6iuG2RJQlQq6TygcfKzNCYRsSHk5/XG3duV9l1iSVq3n9y0IrBa2bJbJKh7Cm4tG/b3uBZtaCgBX1Ud9rj2s5kUxydUqz+HxAuYTKVWnu2X1vLVgA9rLSOAk0sw7R45WG57h+Ff2dSPHBTGxnZ6NogaNrf3JcKp7pbCaouAhIBtFgtz3kUKF4xDVqpxum8XCq3tigvAwdV/gKWEiF5jq2znHe5HmNib91Z/jfXiL8zxukQv93swKVwA6Nz6Hjq3vpqg75UK+pCRMWqubwkMiG6G904vtsxfS69x1XOQroh5X36Ce7PQBlU8oFTp8YuIqp3i0QSw6Q374osvMnToUAIDA8nPz2f27Nls3LiRlStXAvDMM88wfvx4evXqRd++fVm5ciVLly5l48aN9SF7ndKxRUsOdTuNaqsvm3bvZkC3mqdrttXfwla0wwbh+clfZKacx903pE76lK1StSwf1xLQvBv3friEfWt/ZO+qbxh058d1Ikt12bhwHu5BzRp0zKaCd4AHw27pe+Vz8NDOV/7etnMVJTmNY+K3BeOqFTR75qmKdwpl/kEcMwzPwNIXulbhSOeg5vUvoA20cQsiqW8AvbcsY+S+HOL6NjHlw4YIIGtJJsW/9Uc54G0Mkbdd/4AKkGWZnUt/4eCRY4yb9ACiuuLolhKTmXnr9nD48CE0Wg3dOrVncOdVPGO18tmORYyd/z989f681HMKbX2rDjG1yJZqJ87qf+cIfvvoR9qkZuPkbftLfOfShSRs38gTfy6x+djaEn/08A0RbmuT8pGamsodd9xBSkoKzs7OtGrVipUrV15ZXhgzZgzffvst7733HlOnTiUyMpL58+fTo0eP6/TcNBg0oAtLt55k/9xLKJW76dOp0/UPqgBb/S1sRakrNacr63K5oZrLLhUeahFQaRs+5NXJzZ0Tm9dz+sghmrcs7zH+/xFrsRFJVCHJjWxTrQayQknLfp2v3/A/giiKfNWqHWP2HS6XCr5xkaG6lg9ZpmDWIIQeT9RY8QBIObaNbQdO8ND/HsfB3b/c/ks5hfy8ZANZSecIaBbG01Nux8vV+cp+jSjyXK9beLbnOOYe2cnTaz5EKcLjne5naETFGaAlWar2MoqoEAkPD2frkg30u20oWserypG5xERRZj4X8xPIFwuJ9okmPiOehLwEnA3OhHmFEd6hM7tX/l1vv7EkSaQdOE1RciaiXona1YDKQYNSqeHi7gOER3bAmmdE4VQzS3oTiLS1Tfn46aefrttm8uTJTJ5ceZx3UybIx48eT+SyYmYax2YUsG/7LCZMGoifR+VOTJVhk7+FjSg1pTdKcVE+ztdpW11qYvn4h/B2/Zk/bQnBUZsIjOraYLk3Og8cgldgEAs/eIsHP/8efSOHLzYFClIyEWQrUonx+o3t1BlpxhLWpV5ga+YlihS+tFk3m8MDb29ssQAQqf5LOWvFHeDshVvrmvunyFYLi/9eSddAdYWKx6/LNnPs8CE6tm/HmImPVJmRWBAEbm3VlVtbdWXbxTje3/Yd72z/nGaGKERRwt/Rm9ta9EeSZX7cMZshRdVPr96qV3tmffcrs76aSZG5hMjAcDKyMzCZzeh1evZpDrBcu4ZQMQRfnR/eWm+KSopILU4lT86jlcnMx69OxiOwGWERrWjVsgdObjVbnrqWi5v2kbfmIoKzEpWHAxitFBdlglnGKpnRFSrR+GrIXnQWpYcWh44+KN20CDZWq27s6cn/69ouFREdGs7FASkkzAPtSV9+/XoNz7820eZ+bPG3sBWfgEiMwKmdK/AJrn0tA6BWlg9Xr2Z0GDWcYzt+Y9Mfn+EW4M3Q+z5Ara3/JEohUTGo9A7omkjhuMYmft0hdJZCfLv3bGxR/t+QUlJC2x0n6aM+RUdXF1a2dKCF263XP7ChkCUE4fpZPWVJwm33UvJ9a14Koyg9niUzP6FlSAjdby3/7FuwfhfHTp3l7WceRmVjptHuwZHM9f2Aju8vxhRo5NaOwexLPsWUFc/ipW1GZtEOhpv7V7s/R09nHnz5UQAyL6ay6e91DB1/E67+pQrErdzBuEPb+ObAN7wz4C3cXcqG01omWTidepIjJ3ey4/Qm1s6fyYOvfIWPp23RmpJVImntAXKPJCNnm1E4qwl9uA8OftfPJG1KyKdgWzKFey8R8Hb1Vxgk5DpNu18T7MrHNRjNRj57fgmGQncKHLJQBhoZVEkO/8YkqHN/NnmrsMxeAOOfvP4B1aEWlg+ANr2m0KbXFGRZZt+6z5k77UFuf3UWgiCQcmEPR7fMpfOIR3ByrVvn4z0b16NQqRqhiFx5Gvp2zs3PZ9acFZiLJWJbB9O/ZxeibutJ8rF5zJm6kN7jmhE4tGGd4RqCEms+n25byBPdq67g3FD4arX00SUhouOJqAFNaLmlFKGayy55217GGVCNnlmjcZL2r2bt6pUMGnEzvi3KKr+yLHPhUjY7d+3m1cen2Kx4ACw9mMTLi48xrl0Ur40szakyrkV3oNQRNfVSPod/P14j2d2DvRn7SHlLVcfW3XlarefJhY/y3siP8fO4aslRikqifVsQ7dsC+sL7r91FdlEWPlRf+ZAkiWPvLgZnBV79I/FoEYZCVf3XsjrQEaWnDqnYgizL7MktxAqE6jQsTc9hU1Y+BVYr3VwMtDToMcoSy9Nz8Ssy4my2VHuc+sCufFyDUlQiSKU3xf2vDsTNua4WNeoWpUKJdfxwgr5YxIUDm2nWtqKC3bYhS1ZQ1P4FLggCHQY8zsltt5Byfg8unmEs//odWvbvz/wPnsA3ohn9JryBWlv7JRKr1cq2WTO578P6KSZlK7ZGFNSE9OwsLBYLsiDz+yeb8G1loFWvEDZs3MeBDRcZfmd7Bn92N3On/Mbq2QncewMqH/fE3sdPR6czNqYXgc6uTeJl/0enoXTZ9Dczzu3mvvAujS1OGYRqLLtYS3JwXvc1RXf+jt67+lW1/yFu+zKWrd3MlAcew+B9dYJhtlh58623MTl4IZtL8PAPwWBjAUJZlpn65wF2n89izgNdiPKp2KJqleV6WUuIjW7Lq+rXeW7pk7w95D2CfcsnKCsxFWNMSGP31mXs3lkagOHq4kVsTGfCAmO4+OpGJKOVQu9ChCwJSbg8UbFIKCMcib6n5hF7lvRijrqIfHv4HG0c9WhFkVnJmQzzdOanFs0QEei75yQnCkpwVCp4JcyPBcrEGo9XV9iVj2vIKchDVlgp0uShb8LF8AC63/08+35fStFbLxA0b0vtH8C1tHz8myH3v8bfX7+KqdBMz4mTiO44ng6DHmHvmq+Y/c7d3PnW/FqPse6vP3ALCcNwOcFdYyFJErs3H8Zird+EX7sOHmbd/COIgoAq34HuE5vTvUNp3pjWEdHEXTzHwhk7OdMrgQ63RrN8XsOXKmgIHu48gmJLIWMWTuDWsHt5vvf4xhYJURQZ6qHnYF75/CONTTPTFuQqPAyLzyyB+ZOx9H0Ex9CRlbarirB2fVCu34yD19UlmwtpOfw4ewnBLTtz/zjbU7IDHEnKZdKMXfi76fninvY4OFTuZC/J1XartZmwsCjeU77Piytf4MX+rxAVVDabrVqpoedDD5KblY7VZEJAYN/CeRxYvpjXPl+E631RJHyzA5c0D/JDioh9oOISATVB5evA+DNFzDL40T+0Yv/ELZ3LLs/LyCga2VpsVz6uYfHyjRgK3BE7ZaBt5MRn18NB74xy6n0Ev/4da6a/wOBHptWoH1mSMJ4+gzU3r06VDw+/Ftz9zgIkqwXxcgZAURTpNHgqGQnn+PPd22nd7yZiutTcoz4rZTV+EXUfymwL+7cfY9PGzbi7enLvQ3fW2zhJqalsmHeU+54ejINGz+FTp+jauk2ZNpHBoTz6gi/ffTOPhFPQJbao3uRpbJ7qPp4CkwmLZG1sUa7wdFQPWmzaRsSpHUyNaDoWp4vqHpX6fBQmb0L/+x2YHlyNo0/NIo9kSeLnL94po+AcOpPIrL/m0a1bd0b36VijfpefT+fRZcfQq0TMBiXPrzxJUloh6x7pjr+DptyES5aoVy/KgOAQPhr8Cc+ueorHez5Fm/CrFiJRFOnXsWxdn5uG3ce01+/m5WdHE9O1L63DI8g8dQm9Z92GYQtKkd99fDh6IYf+YdUPjqgDQ3etsCsf13DrqEF8dXAp8tnGdsWpHt1ue5z5K5cQ8fUS9hWqaPfk6wjXSY5mycgge9kiSpLO4DZgLDlrl5L367x6k1GsIPXwsPs+Iy3hMFvmfsHpfasYet+XqDXVdxgtyItn3azXKM45T7Ob7q1LcavNkb1xrF+zEUeDC3dMvg2PCor71SVLft+JbwsDXi6lznD/Vjz+QatWE7P2c3Qjh9H+oTfrVabGRpZlmxLj1TeOKi3rO7fk8UM7WHRpMWt7jKzTJaFZJ5Lp7e9KgFPVFWGriyxJWP4cS1avSbjXUPEAOLN9CSprMY+98umVbaVLKyIxYbY7r8qyzBPbTrMhr4BlEzsS5Vqa5v7+FUc5dyGHnu+s54+p3ejmV/aes0pytfN81ARTUhr59z/N8xYre1c8Dg88T5v+Iyptr1KoePmtWew7tpnDWzbifMGANKU5QeF1n6PDCqhsOHUZEO2Wj6aDQe+A6GJBztBiMptRq5p22u79l/bzbq9MbpVFRs5cwPHNh2j2zts4tK4450X+7m0kPPQQlFgQrDIFvy4GwGFIX5wHDEfpbXtIcU3xCmzFzU/+yJ6V3/HbyxNxC/BGoVCjVGtx8fUkKLYTvsHdUCiuWqAkSWLDnJeIPxRHh2G3YYhwbHBH0xOHzrJmxXp0WgfG3zEOn4Da1YeoLnc+PJAv31vIpoM76d2mcp+C5fcNJSi+EJ/hTSPMsz6RkRv9Afpvwhy9WNpjFJN2LGTqoc181bZPnfT75o6zzFh8EidvPX1ivPhoQDRqG0Mr/03uqZ9xybdAv69rdLwsSWya9TGnElIZNapsBtMwf0+GDRvC7wtX8ObUu6vdZ0qBkTGbjhOk17BncJsy5/jdkFjOdQ3locWHUVeg1EmyTH1eDnkrt+DQozc+Lz6AYdl6jk1/g4Xb5jH42S/RV+HD1j62F9ERHdj76d/0DKufnFeuKgWJNjiQyjKIjRxsa1c+/oWTrxbrRTcSLqUQFljzkLP6RpZlnlr1Bg5KXyZ89gdu585z4elniB9/G3JEBL733YfL0CEIKhWS0UjW3FmkffwJChdnwtb+jZSfT/HhQ6iDm6Fr2bLRzqPjkAdo1ed2MpKPYDEXYirJJzMxgV2L5pCf8RWCIMPl7IxWs5XA2Ejuenceoiiyfv1WmzI31oYzxy+y8u+1qBRqbh5/E/4hDZvB0kGnZ/JjQ/nl21UcO3iBe24fha6CrJFux5JxXfwn3kFRDSpfQ7Dl/HFWntmJIAgICGxK2sDg4LpbO69LBngH8ub5bA7mZBBpcEZXy4SAMxaf5OlxLbi/TSBPrj1Bhy828eygSCbF+tW4T5fZT5DRLJSaZqZY8vVLqPTO3P/cNIQKcnW0CQ9k/cILZBcU42q4vrVm0ek0nj+VwLNhvkyOKn9eoiAQ7qInr9CEq7b89ykh19vr1FpUQu6ixfi+U5rYPWB4P/yH9WX3jGlsGj+IZs+8SHSPyv1lVIKKwGxPMtNTcfPwqnMn6Q6h7nwel0xCZiGB7tcviCgDtdRda41d+fgXgggSVvw8G84KUBNWnt5LBucoTphEr2k7GBzhzLdr15C1ejXJP/zIpWefJfGdt1G1ao588AhygQl9vy74v/g2SldXcHVFHVSxciVJVnbu/ItOnW5Gqaz/hGEarSP+oVfT2TdvDVwuUitZLaXOUYqKHt5yvSsfF84ksnzRGpAFRoweQrOI8kmTGgovdzeeemE83/+ygFlzVnLfHeVDTYudNBx66xmCfl7TCBLWL9/vn4dVlmjlVeo8N7TZMMbGNM18JneFtOds4XqePLieVKuOWW3b0MatdtW62wc4o1GKfD0klnNdQ7h/4WF+2HGBb8e0Itq98mXLihaRTQWJqAH3O/fZLogs89UHr5NRrOH1R5+vtNmf6/bgEtLiuoqHJMk8timOrcZilvSIJsK58oKI25KyQRQIcynfxipRL5ZQyWwh/u7HcR4zBn2rq2n9BUGg873PkzZ4LDvffYpz33yCy/jxdBx6F+p/TQxUShXJjpkovt2Go1GP85QoAoLrpjQGlPqcGDRK5BwjVEP5AFDYLR9Ni5xDQEAauiYc7SLLMh/tmg4WZ9ZMeYg/dsbzw7aLJOYaCRw6FPehQyk5dYqkH34gc9c6Mpr7oRzYHvdWsShJwk/yQRQrdkBLSDjIkiWzAQsHDx5izNh78PWJbNgTvIaKfEb+QUaivvzbEy9c4u8Fq7CYJQaP6E/z2MazglksFqxY0Sg1CIJAbqKRURMrdmgcsGYff/eLZVX/1gxed6iBJa1fFKKCMREDGRvbdJw5K0MQBN5qWZrwanvaBe4+eJCD/WqnfEjWq2pEqLOedXd3YcGpVCb8vpcOIW58OTQWnap6+TMUn8SSH9YGRxtn4HvmfcbJMxcIctDw8DPvVdruTHImF04c4q0nH6yyv+MZBQzfcRJfRw07BrZC+y8LSrbZglYU0F3e3tbLieJiS4Xp661WM7Jct7krTBl5JN7/BIa+fRBC4cwrd2Ex5+N357M4xZQuf3oFRHDTN0tJO3uMQ7O+ZN3MXxD8fPAadhMYHLBkZyNn54Amm+zMCygPF2FU3ETAm/fVmZwlRjPxJhNGV5EV8ckcy8whWKtiXFR4GYVMlmWWnT5PicWC2dS4WZDtyse/ECQR5SVn/li0jNtuGlrn5jFZlvnwww/5/KsvSU9Lw83fmx4TR9F7WD9a+QTRzNUXHwd3NMpSX4cSs5H9yWfZm3yaE+nnuJiXQLrxAiXK04wLeY4QTydGtw/kh20XySo0EehWOiPQRkQQ9uGHhAHFxZmcjNtFWmoCJ06sAFYyadKrFcp36vQuSkosuLlp6dZ9AAsX/ESbNu3o1q3mUSn1h0xdL/KmJqezZN4qigtLGDi4H9Htysf0NzTTf5iP9YgTJd5ZKIo1CFqRqNDK5erz52p2TK66iuh/EQGqDBltqnTzaoZWOMBf8ce5NSjmyvZ8kwWNQrzi15BRZGLgTzswyjJKUWB4C19e6xGOVikSHuvBlPmHODa1T5m+x0Z4Myrckxc2nabzl5t5pHcYD7Qvqyhfe4fIkkTO/GEIBiXOEzfYdB6yLLPsaA4P33oLXjHdK20nSRLfz5rHLSOHolaXt1jKsszSM+l8svkMBcUWOrT3YqexhAeOX2SMlws7cgrZnVtImsmMUhAwWiWGqrbhrAtg2wGZvFQFo6cvwknMwWSRUIoyVhkURpHHFRqgbpTTrDN7iH/xPjQnTBSrj6PICcR5+AiKDuwh8ea7cf/mZbz6TLzycvcKi2Xgq98iyzInDq3j4t9/oTBLyM6O4OKEItSHoN59CH+6DWkfreXSh8vweKAvSqfKLT3VZc+6gxRYCnlp92F8RZkwBz1/p5Xw9fkUlAL4KhU4K0XOmSW8kOgkWZEsjRspZlc+/sXoJ9oxd/o2slf6si14Pz3blk+4I8vydc17WUX57Ek8y96kcyTm5OKiF7HKFjb9PI9jW3biMcGZEO9mFMYVsuC9r9lvXoZD1DXmMkmLIGuQxTy4nJBGllSoZU9cNb4M8nmSV/uWpn131ZcujeQUV5xnQqdzp22bYVc+L1jwHitXfcGQwVfTHxcWZrBkydd06TKAbl1v47vvprFwwUqefPJ1Fi3+gN9/f4NbbnkKjQ1RKfWPFbEaaaOrQ0ZqFkvnrSIvN5++/XvTqnPjWXv+TXiMH8ku6Tw+YSKSJGM2Vj27Uzk5430hj+Wju+D7yFTaNpEaI//G1tp3giAiIWMqzsZoNWEyF2IyFyJbTYiSBQEFaq0Lru5Nr+LnqyFR3L8mg/eMmykqMiOYJHQG1RX9WQaUCpHOoW608HYiJbeYRbsTmLPlPL7eDqRnFRMRWnFElUIU+aBvJFM7BnP/kiP8svsiX45uSXtfF+DysotkIf/g11h3fIHkG43b4+kINk6sBEHglq7BnD20vVLlQ5Ik3vphHoFBwXSMLfs7LDtxmI83bCW10ItcR08mtTfwfsduSJLEyow8fkhKZ2ZSJtEOWt4K96ebqwFREMgwmvh922u0CXqJwQN1ZHSw4K0xEenXHUe9FyaLudT5uCiPpHmrbTqniijOT+bszs8xmtOI/XENKr0LimuXn7vcScGIIyR+9yaZc34h5tuyS5yCINDMvxnSim3EbDlS4QTW/93xpH02n0vvLCZg2oRayStJEqcP72XFQ5MwOJd3fC2yWDiRmk5KfiEuKiU9wprx/er1jV7cxa58/IuIoGZI2k0UqfJwcgvneGoyR9NPsivpKHFZcVwqOY9RSEaWlYiSIyoc0YpO6BSOWIVC8i2ZGOUsUBSU7TgPJKPEiQUnCHkuBF2oC590/4W2vqE8ZX2Y1ONZjB/zFOnFmWQVZ5NlzKbQVIirxpu2vuF0DGhOC+8AFBUsl7g5qBGQScjIhwjPcvv/zejRz/HXX2+zcOE0Ro16BlEU2brtd1JSzCxevJjg4B3ImGjTNgi1Ws+tt7zO/v1z+eGHN7npptsICmpXV193LZGp7R2UnZnL0rmryczMolevHrTrEdMkUrVfi6nEglr3T64UAY2uaudFjc6A9ufPMTz5DAbn618P/xVaeEby9Z4v2L55H1onfzSiCpWoQBAUSIKI1VTIGnM6W+85Wu5Yq9XChQObSdq/BaG4hBa3PYSrd8MtpX22Yi+3hoUwtXN7mjnpqnWNvdM/CkmS2Hspj3yLlZYeVSv+AQYtK27vyIqLmdy/4DBRngam31TqTF74Q1tkUyG6SSvQuLeo8XlED7iD3z58lg7FBah0ZeUpKDYy7cfZeLi68Oj4q0nFJEniiaXzWLzDgU8mdaBHs0i67dzJ/Jxc3qc9oigyzMuFYV4uFY7poVHjolTir9XR3D0WAsru114uZGksAjlTJGH5YoRTWajE69dGKUXAdUJPslJ3kZK4EJM1g0D/u/FtPaLS38kQ2JKot+dy4vERxL16G4aOPXCM6oRkNZG+7BeM2w4hGKnUci5qVAg6HbpWtZ/MbZ27jrCgkAoVDwC9Ukl7f99/bW18C6Jd+fgXsixTmA96WcEjK+4mV5deul1SobL64aEOJdR5IApRJtuYRa4ph0JLDnnWZERZj4c6DG99N4Kd/Yj2CKG1Tyj+Ls6oRBWH9h+im7kbqZ+mAqmMpXTN0GQy0bZtWyZ3qlnCLK1KgYdO4GRyTrXai6LIbbe9yspVXzF9+osoFAKCYOXRR98kLe00Fy8eon37vgQFtb9yTLt2txAU1I55874nImIfffve1wRe0jaUCv8XeTn5LJ23htRLqXTt2o07HmjVBM6nLFarxO5DRzi+M5GA2OrnEdnz9wyyfviB9n8txKOCVNBNB9u+7ye7j+XJbmM4/V5XxD6fEBbTnoyUeJJ/uQdZEFFbTaS7lrBtz1dglVEmmHALiEXt7MqRP75GTk7F0KsnWbv2cNTLg54Tnqqn8ypP2yAHCvJTCKnCmbIiRFGkk5+LTccMDXZn8MM9eXPnOXp+s5XDeYsw6XSonk5AqNBx2wZ5FEpax0RwcNlPdBz32JXt8zcdZOe2LbTv2JHbBl4NBf913zZ+3X0cB7WKPS8PxtPgTEZJHi6KEvb2HVXREBXSq83nbDk4ldAecyqcgAGonNxxGhRI+uo/UCTJePWpnsUv4dIfnN79CR66QUS0fgEH32bVlivi/Tlk7V1G3oEt5G1cjSCDU78hhP3vS05MGYilIAelwaXccZbsPEwXzLjeUnFaBFuQrFa8fBs2+q4usCsf/0IQBIL7xpCxIo2bDj9LdvdsurWNpmezKFz0tXNCFS+/KJctW4a/f9moCU0tM6pqlQJFJtucrYYM/h9H/Vfh7OxJYGCpNcPfvyX+/hWH3np4hDFlyjssXfoxP//8Crfe+gQODg2T56JCZMlm03FhfhFL560hKSmJTh06c/vkMU0qUdU/zJq9gpSdRlQxhXQe1pxurdtW67hL545S8MV0esxbiYNTI/421aIGsy9BwPXuOWT8PIE9m1vgmHkE/ciPCW/Vjb1r5jD43AwSMuNQxccT+vMFTrcLRbrsU9Hlza/wDGjOyhVraTF0UrWHLMzPYuu0pxAOHkc9Zjh97q3YX6oqDsUX8MzAhrMYioLA613DeKhtIAu+cSBI509I9lncPWofgt1yyN38/smLtDOVYEHBV7OXk5WZzkv/uwcXp9KZ/PmsTCb9ugQ3BxX3dmnDbW06XFHuPbROmGQRqyShqOb9G+rkxy6njqy7uIpBIcMqbCOKIp5te5D+13u4jZqEa//qRUKdXvQm4X4P4NPW9uUPhdYBzx634tmjfBVjVfNmZB9ci2ePcVe2SWYzuX/vomBLEtoIJ9S+NQ10vgYBigptzGbc+IYPu/JREQ8N70hS+wJ+f3s3Plu88G/lV2vFAyAmJgaNRkN8fDy9e9dtWnC1QiS3yHbv5RYtbMuTIIpKRo16jmPHVjJz5jQGDRpBRETtC9vVDLnaxdyKi0tYNm8tFy9epF3rDtxy50gUjR3oXgVde7Tgr907mTR2ED4e1V86yR52C8Uj26DVV1x860bAwy+Y/Ft+RDCZiYiMQrjsnC2d20hEp5eJbNsTKe0cyWvuoe1XC8scazGWIFktuLpUf6YYt/VvTHGn0JslitNTbZbXapVIy7PSP7zmyx01xVur5gv3QUxvO4RLv4/iXGhv2g77EqWy5pMdhVpLbPNgZv3yA0czICKmJY9PHEGBycTw734j31hCXpGC10a2YExspwr7kFHQcdMy9vetfi2ZwZH3cmBHZ2amLOGebt9W2EaymLEmZiIpql9nSVfiiVKsO1+2AlMhKUVpJAb7kfnjn5xYcxxzTi5SXh7R3qUlGFK8/MlQ6BF+2I+qxIr8zwqyLCMpRSR3LQZ3HWpnDTpnDQatCietEietCqVSRFCJoBA5sfUgCYmJ3P743TbL2diWXrvyUQn+PgZ63R3N/h9PcPxoBu1a1j7vh6OjI08//TRPPPEEkiTRo0cP8vLy2L59OwaDgbvuuqvGffeJ9uXnnQkcS8oh1t+l1rJej9jYIQQGtmbOnM85cfIAN42c2ggX8/V9PoxGEysWrOfM2TO0jmnHY88PRVmDct4NTWhAIKFDjvD7d+t45KnR1Q79Dj20jwtfPM+6kd0Ievl1oroPr2dJa0PNr5eQ5qVRI+eO7SZz7WcgS3jnHcUrqjTFtzU9FWt++dngiW1/I0WH2TSWqFShahWL8fAJhj1vezbQwymJGHSNO9UMjh6DtsU4Dq16irgvW6Lo9ypRratv/fk3LYfeyzvvzuKLR2/GwVHL/xYuYNfZAu7q7s/41l1x0qjQqyu/ZmXZwt9dbJu0uOk8OKcbSZtmlS+nnLitJ6glPLo2TLSX0WJmWfxmllzKIEvSICCjEWXcleAZ251o9264ejXDxd0NV1cX9A46nEQRd5MVo9mKJMnoHNRlQqSLis2cT8glLaOQkowics/nYjZbsZitSBYJk9FIYm4cVmshHo4u3P7QRBSq/96r/L8ncQPxzfT9yIdysCDTt2/dOaa99dZbeHl58d5773Hu3DlcXFxo164dL774Yq36fWZYC9Ycv8Tjs3az5tmal2e2BScnXyZPfpNffnmTTz99gfvuexwnJ58GGRtK83xUVjDLbDKzctFG4uLiiI1sxePPPoRS3fSVjmu5ddAwFinW8vU383jy8durFfat0egZ+swXZN55kd0PTGhw5UOSJEoOn6Zw+0FKTsZhungOzCZQKFB6eaEOCsLQvzeG7q3JyC+p2SCyjCzL7Fs3lw7bpmC6eR0OWhVZaSkE67RkvfsIhbv24vvx9HKHphzZiXLHQZbf0vOfILKqo25kUBaWIPTqiLLQyPJbrpryFQH+hN5+L807DqxS3BVxJ/Fzqjz9dkMhikraDv2cvC6Pc3bBXezZPZ3QMT/VaClGrdHSzyOBLxYtZEOekqEt3Vn+8AB8HKvnm5SDC356F5vH7Rp+H3vP/khH34otKuHfLeTc2/dz6o07iX53gc39V5dz+Rl8ELefhOJCujlreK3VIEIM1ffLUupEdJU4jut1KmIjPIiNKLskI8syP+/ez/E9hxkwui8DoyOaXHkBW7ArH5UQFunGmUM5lPhp8fepO5OcIAhMnTqVqVOnXr+xDWhVCsa08eXbrQl12u/1UCjU3HPPWxw/voZff/2EAQMHERU5oIFGLx/ybLFYWLt0C0ePHSMyNIapzzyAuoJUzP8VRvcfwDen5/HJm3OxqE0IZhGNj8xdE0bi6uRc6XHu3sHIOjUFuZkYnOvP90OWZYoPHCNv5WaKDhxEKshH5RuArnULXMYNQ98uBoVBj7XYRMnJeEpOnCHr5z9Ifft9AswFPPfFDjoHuzBySHNUmqofRyZjCfvWz8Ph4AwkUYWs8+RQp49p3aI9CAKBzVsjW8zkb9hO0Kp9FfoDDXrsI3isgs6vgyRJiC9c7c8qWTm6bQl733mGooefo/Wg8v4C2cUZfL5+F3N2F/Lzve3L7W8snFxDaHvvZs4fn0/yrDHEB3Sg5YhvUGqqpyClJ+8jY85ttPGIoUAfzPRhvekYaJtjs6eQXRPRaeHZgj0nUyrcZzWXkLnpL6znUwn/fn6N+gcwW40kFmahEERUohKVqEKtUGKxFLAt7QSr0jNJMsJzzdzo7N+/0glQXXI05RK//L0CD3d33rh/MnpN+czTZnMxmzZNxWLdiUo1iL59PqzzPFV1iV35qITB/Zqxb30Cco6psUWpNo46NUYr5BaZcdY33AtXEARiYwcRFNSWOXM+4/y5Qwwe/HilWVTrjqvRLlarlU2rdnBg/0FCAiP535NT0OrrPzV8Q/DQAzez89AhokJCMTjomfbmLPKyiqtUPgCMSpktf33C0PvfqVN5jBeTyF+zg8It2zCnpqDyD8Ghe1f8P70FTUDF/ikKnRqHtuE4tA3H/fYhSCYTDqdScC9SMn3DGSxmiVvHxVZ4bLHRwtEP+qNRKVEH9SDy0floKpllyoW5iA5amx2Rr8e/H+IKUUHrnmMIDGvNtql30GrgbQiCgCzLHE1awZHz34I5leUHptLcxUhC0jk6B9m23FPfhMTcjBQ1mj0bX+P0122R2txOTJ/XECq5b2VJYvfKqTjGrcJxzA9EN+tDTZPby0CJ1Yy2BtE3glDxa+vUmxNRagyEfPMzWq/qW6tl4IQxiz1H/2ZXrpEiWYGPstR53yqD+fK/MkpiDTruCoqgvWdMg7zYS0zZLD/wMdaETXTz1KJRq9i47htEhQKlIhBBXIPJ1B6lwoDRdB5ZEvDze5zMrGls3iwSFX0PBgd39HrPMvJKcgmyXH2/mPrArnxUQlGxGdki4VIkk3SpoE6tH/VFn2h/Pl13loEfrmbWAz1p7tOwToeOjp5MnvwWq1Z9y4yZL3LrrY/h5FjzwlfXI6uwmB/nr8Yi7ESbnI2mxAOcW3MhTc3Bk1l0addwS0D1iSAIdG3TBoDTCefRaTUEN7v+ubmPGE3OhrVwf+3GtxYUkbtiCwXrN2M6fxaFsxu6Nm3xfPxBdG0iauTrI6rV+LYI5vX3N+GhUxEWUrnJetdPj9HZchzty2nXHatg8a9ofBsuysfNLxR9Mz9mzeuF0lPEbClGqfEnMvhe2geN4vZ+kF+Uyz0/zmdcE8wKL4oKOvd7m5Luz7Jv6UOc+LoNQXcsw+AShCzLmCQT6Ym7uLTpHfSZ51EFdCBq6nHEWobsDnJ3oOum5VhkgU09BuCmqV2Wz9y4bUgX0wn/ZZ7N1+MSVW9OlTgw0sOZu8Nb4aatWqlvSIrM+TgX/knLwVvwuvwslSSJvLxUcnPPYzTeird3NAUFabi4+OHgUKr8p6f34OixGRw6NA2zOQdBKABUCIIBWSpEFO5CrW7cHEB25aMSvnh/Fy45VgoCtPh6VX5jSFaJ+PNxmLIT8QyOwdWrfOExWZYpMFowaJT16pQZ6mngmzs6cdeM3Qz8bAt/Tu5A14iGjf8WRZGhQx8mLm4rv/7yGQMH9iMycsj1D6wB8aI34S3b07l5OOYSEbMFtBolOTklbF5+nnVz4nBp5oiXpx4R0BpUtGjlRbBf46+/15RNWw4Q3bV6Cl3PWx/n743r2bPiZzoOvbvaY0hGM/nr91GweQclR/aDKKBt1RbXCbfg0L0VYh1GCZmsEm881Am1uvJHUeSQhzn1VxwtrFYUyqofWVJGEubMvDqTrzr4jQoG035i2q3H1ym43H6DzglnHbyz8E9eGlO7bJb1hVbjRPdxszh5/C/O/zoEEJCF0vQAFq0zzt0fJzxqbJ1YlPZmxvNrlgcIHriTjFiJJaMyKnLdzdm/BnF3us3P1/v+XMJF/PnaP5aI0Lor9FYXyLLMtiQNv5x/kr4Fb/PITd8Apc9YFxdfXFyuJg5zdi6bRMzTM5K+faaV2Wa1WjAac1CpDPy2eX2dl6awFbvyUQlihpF8bw3Pv9ytzPYSo5GjO1ZjiVuJU/YxfEvO0ozSh12xrGZes+dJ9h5EwqUcErOKSC4wkVIiYELAQbYQqLYQ5KRB7+SASqlAJYJKFDDo1KgVIocuZHA424KTXk24WIzBxZHxg9qQV2zCWFCESqOm2Ggm2NeVFv7OiILAhcxCdsSl8uWKo6Rar/6ki6d9TUEfV0RRRBBAFEqvN4HSPACCULpoIVzeLgrg4ORCzMA7a/39RUb2wM8vitmzP+fv4ycoDAmjonQaVRXBrio+4HSRiX368UxrFkZ4QPlIpE5tfTCZrKzbHE9GVjFWGTKTCzi6LRlJFJj8v7Z4e1av+mNTQZZl0k8WM2FM+ZT/12KRLMQnHcdT54lX30EYnpiGZcDtKFVll6GsJWZOd++HOqg5iAqQQTabkC1mtJGROPTqis8L96GoR2dJGXj+650oVQqeurUl3l7lLYy+obGc9+7ArhlP0m3KF5V0JFMw7xvyN2zFafjQepO3IqJ6fIj8RwbGfbOh73Pl9guCwE/3T2bUZzM4mXiCqIDoBpXPFqJiboWY8jkr6pJ2bgFsaivywvH9WCQrLurKl0eLTSWc2/cXXs06UWCFIN/wK47C/3B2/S2kOR3CSSeS9vydeL3/a7VlybNKrJl0U01Ppd7IKDIx4uddGJzUvDhwAhePvsS+05tp37zmaQ0UCiV6/VUnVnuobRNF9tbimGwkv8CESsrnzOY/MMatIzxvNx2EQjJw4byuBccCxuMW3hm1RzDuC8Yz7uKbtD8ZjKdKwE8n0stTS6CnIx6eLlwyi5yNTycxPZ/U5CzMEphlATMCqRYFSiDaIJNhUVKYZ8SgF8lMyGfB9zurJXMfDxXvD29Px1B3DBolyR9swrj8T3RTn0KWBSRZRgZkmdK/ZZDk0peaTOnf23buqRPlA8DR0YN7732Dpz//EieDSLfoipcKrtwCFRQNq+z+GB/ozov7ijDJlc/E1GoFQweUn81s3JbITx/tpe/NzencwafRnLLMFjMfvzcbq1kmtJ0n3bu2JjU9k6zcHAZ378mpi+eJu3Cezi1bs3nfHpITM9G4g4OuckvchWM7OP+/hzE38+WoZEQREox6+utIOUVkb9xC4e59GOOOg6U0AkVQqfF99yXUAT4ggqBSIVbxMqhrvprajbzMYr5ZdJykxLwKlQ+Atre+xIXPKs9JU/DX16R+Pp3gX39FGd6wzp2CIODdfhJJe8pH11zLtHHdeW7uNib3SGBk+wFN2hmwPhEFkUiXAIqs++jsUqrYJiceIyXxEKFR/TCbjRzd9Qfu8ZuwKjQ4qZSkHf6LQoMfQsouvKIUmAsSURkCKDi3iAvsx0Nwxuemdog2ViOvavJTX0iSxPeHEgly0jEsrHTpI99oIS6niHM5hayKS2f3mQzu6h7C051Ln1+pjq+yetsDRAa0waC7MXL42JWPSujcP5hjv51i/+uP0tVhHtFYOaWMIC5oAn6dxxAQ0w2Pfz08jHv6wcV57LvPGcL6Qw0fLv9U7hQEAbNVYuvpDILc9XgYNFisEqIgcCYtn8Xrj5CPklt6RhDl54yHoWziIL9nPyDtmbtQrVmJ66szqzX23r17ayRzZRRYrCgNjvhp3RkQUPWM3VaUHMUoSzYf16d7ABqdgm3r41k/9xQO3jq69w+mY9uG8RH5dsY8ci4aEXN1OIU5cMeUQfw1bw1//bYRtaNASarM/jW/I+olHN21HFq9HJ2Lgtadw2nfuupZc+65OPRFVgJ9+2NOT4dEAcvHf5Mg/I2udRsc+3TG95WHUTjVrw+TsbCES6cTSz9I8uV/rlEuL2u+okZJYMtQHHRKTp7Pxt/fCW/v8rLFfzYQs6HykvQOo+9Fev8LpMLiOj2P6iKqVMjXSRsZFRDJ7w8G8s6iv5izZwY/Tp6AXvvfsr7VJSlmgTdaDiDp0mlMf07AEjmWM0cXYFY74R41hNZDnwFF2VeULEnoTv7K8S2j8XTuTmHRGRAhtt18Lr41nOD5yxrpbK6yKSmbPYk5PNwuCKUAHT/fhKAU0WuVSJJMiclKmI+BvQdTcfbQISpFVEoRZwc1rno13UPd+GhwNK6aq3413q6+BAbey4It73HnoPfqSFK75aNJ0qd7AJmzFxNf3AtVpCu+A+4nOqRqb3XNqJeRP1+IMGscFpU3wpC3ULQfb/PY15rDVAqRvlHllxU6hrjT8d4+1+3Lc9pMEkZ2ovoR6HXLb3Hn0CfFc8pk5vmz53jwpmE0c6sbaURqniW4aztfurbzRZIktu1NYeOqC6z+Mw7XKBfGjY7Ay01XJzJWROE+DV3vasaB3afp1LcljhoD904cc2V/WlYmJ06fo3fnjjb1+/n89xn00i+owlsgm8w4DuyHNjIITWQICm3t0vfbyrFNBzh67Cje7lev3SvX9T+XtyRzJuE8t/ndwYD2/izeHs/xOUd4e2pZz8wdM5+jq/kExgfWVTpeyfZlOER4oG7do87OwWK2cHHOGvIWLiDk3VdwiSwfQSFJEqmrtpF5Zjuy4fqKsKNOz/sT7ubvfRu576fZzLj/drTq+rvWGhNJkjhx+jwWyYJCB4u+3U1kT29GDepLWl4umZIfm4+dxmnbM6jH/UrnkDbX7VMQRbxj7katFDAXJuHt3ZOwoGEICi1uYweTfO84glbsq/+TA0rMVu5ffpSdR1PR61X0a+FDeqGRw+eziQ5wpuOWcyhEkR6x3nwzJJb4vGIUooC/odQ6s61nDu29nNAqqzdJbRfelbMJf9sko9VaRFFxPI6GsrlcKjAyNzh25aMK+j7Yi7++TCL5ZCwxvasRluQWgvDsaeTUo7DgWRRLp2CJW4vy9h/qX9hKyP34cTTB9Rdxcj0eaRlJceRLGM1mNp+7wDdz53PP6FFEezeNaquiKNKzkz89O/ljLLGwfPlZfvpwD4JBSb/hYXRqU/cOu1JYDkUFrnTuEkvzgGbl9nu5uePV2baIDYvFwvqczfRd9DutoppGTonI5pF0Hl31GnXxV7OxFpvp2MEfb08Hvl5wrFybrvdMY9f7RwhKuYBvSPlwXKkglwsPvYJLl4By+2qKubiEw+MfRBkeieDhzZkX3kFOv4R+5Fhiny3NRJyfkE7clCcQgpsjuWRjbF59JWJE+z6YrRbu+WEWM+67HV01oz2KjEUYzUZcbUhoVd/sOnKIo/suUFhQgklVRLNwX8wFMgln0xEuOCJ6mDFnKJCUAmlLlXyyYy7IAq929qfX3P4cafEoMdVQPK7FNaJsNuiSrUtJ/WUFvvePqMMzq5y/Tqbw9oqTDGrty76n+zJt13mSs4vp6O/CjBEtUSsVnMwqoJmT/opyEeRU9vrobmPBQJ3GBSXXd6a+dGkJCQkzUandMZuzUamc8fEejY/PTWRlbaOkJAVJUjS2v6ld+agKt9iW3DQpl3Vz8pj9yQUGDjtL2E3XyRjp4I4Q2hvl07uwLnsF5Z4vsExPRvnAklKnvgam+ORZPJ54vsHHvRadWoVOreKmljF4GhyYsXAxPs1CeGpI/1r3XZcavEarZMzYSBgbycEjaaxZepa1s0/SvIM3I4eHob1OKfvq0r5bBAd2nUGpFtm4/BDezQ1MnjDm+gdWQU5eFmpR3WQUj9IH2/V/HJVGxd9/LkajVFFgFVib68bYD5cQ7WPgnTv6XWmn7/4g57fMwTfkzXJ9WC6cQKEDlwl314nsJz//A/P3H+L09Bs0v+cmLMUlpG87RH5iBuZjh6+0O33XA/g+9gj+o/pzKeEQJw7NsWmcMZ0GILCWKTNm8eO9E9GoK1dA4tMT2Xj8MH/uScJVZ+WzSWPxcq59yYfasO34HjYuPYpWqSWyszcBXs0x5cucPhuPrLTSunMInaa0xNXgQmFxEVq1BlEUsVit5B3ejmLJVFI6f0vLobWPAFK36IJCK+I0pfz1IVutWJPPofANQbhOtNT1mHk4kW82n0OhEpl/d2eau5b+Zu/0iijXNsqtbpc2VUo1YEWSjAiCukKHUUkyEnfqNfS6ZrRp/ePlbSb27Z9ASsp8nJxa4ujYEqVSRKFo3PQRduXjOvj16MFtrfNY/f48Nq10I2SIGVFdvZeQYtibSHpnlJveguQDUMc+D9VB5eOJ+cJZVC1qmg6obukaEkznKZN57c+5PPvdTzw14Va8axxNUX+qe5uWXrRp6UVmbgnzF5zio9e24errwJjbovHzrd1N269LZ/p16QzApex0fvm48uWE6rJ93RpyLDkcOL6LtjGda91frRGEaq2JDb5nNOZi02U/J5mbJQkZgUlfr73S5tjBHUjbv0QbVXEJdlkWUWgVqCKqV/n3esjT30IJBI3uC4BSp8V3QGeS+owl6I0XuPjncgrOJ2OUNZglxWUZQKjBIuDoTgMwSxsY99Wf9I10ZXi7TgS7e6G97PR7POEkn6zcQmahSGt/FXMfGc8Tv//B16vX8sYtldc4OXfpND9v3smv+91waWakxGrlfEESfg5unMxJ5Ke4lcRlHsbH4MfDsRMIdHAj3KlqZeb4+dMsm7sLa7EAkoDeVcn4mwcSHl7W4tSpfXnr1LVO0iqlkpKD6/CSkzBpa5ff4x9EF088J40g880peLz3+5Xt1ksXSbp3HOZsI9oQb/xnranxGM3fWU2AryPz7uz4f+zdd2AUZfrA8e/M9uym9x5aIEDoofdeBEWxYuWsp6dnOX9nPT3Pcqee9VTs2BUVCyCiIL330EtI771tn/n9saHEJKRCAr6fO0yyOzP77ia788z7Pu/zEutz7ofKCssLCDEeZPv2q5BlAyGhM4iMuApZ9pyPCotWkZ72DgkJzxESfCo5W5b19Ov7HrKsR6PxvN4azYZmT3FuayL4aAKdtw9JsxNZ+G4Fh779kYSrai9apKoqzz//PG+99RY5OTnEx8fz2GOPMWfOHOQBV8Hqp1CLjyO1Q/DhKipGboMVeduSLMs8NfdKPt+6g+c/+pTbrphDt5AWLi19lscuA32N3HpTHxRF5afVqXzw4jauuKsf3eL8Wn1sm92Bv8UHVVb44oelXDWr/qXCm2LmnGtITB/MMyv/yUN+AXSO6Nbq9rWGJEmNJmACaLQaNN6nPsh//5G+8YO/Yyo5RPT17xEYXn/VSkPiYIKuvZSif/+d0Ld+aE2zAXBOmYv8y1dovWrnyejHTiblhbcx9uqNd9dozH+aS9S0mqn4qtTiWPjyoeOY2X8Q3239jTeWLya1WMujF/Xn2227SM6RefHKsXSPPPX7fOOmm7jklY/rHMftdrFkxyo+3ngUBW9uGR3LtSPCmb28klELJxIdOJwyWx6VFbuIC53B99Ne4fGdX/OXX29ApwvCZU/nsr5P8ES/y04e0+FysuvgfjZvOEB1jsIl148gPi6u1dM0I+c9SXXmjXi/M4YSazb+0+9o1fEAzDNvpPCpv6A67LgyDlLxwfNUbN1P6MOPUr3hN3ShdYOrLaF16zLV55Utx7GrKr/Na59KcYWVdh78+EWuS/RnwIDPkCQdubnfsWv3TZi9uuLl1Ynjqa8xfNhvaLV1L+Z0Or/aN4icj/NHyKAk4pe8z/o1QXSZWoLe79SY66OPPsq3337Lm2++Sbdu3VizZg3XXnstwcHBjBkzBpepK/K3d0L0YCT/ukWIzpbq79/BVViMYWzT5+0H+nix+qNnGXP9Q2exZR5XJw0gPjycNz/9jPvm3USUb/N6QM7lmKUsS8wY14kQXxNfL9jH3fclYfZu/pRUVVXZn3WItb/spTxZwiveDXaZfonNX9zrdJIk0Sm2G72MPShzntsiW/W2B1r/Aae4GZb2JjxRdsbNjgwfhN5oxdS9/iJR7koHGkvTf1fOreuJeP09NL9bP6PPE7c3+RjNZTR4c9XIWVw1Er5Y/xOfbkzmsqQBPHNVvzonep3WQLDZTV5ZEaG+gaQXFvDOyp/ZkWFnWCcDr1x7MREBp4pOJcTP49MhMzBoPc/nx4ztxFpCCDB48frQ62GoZ2r9ypx93LP8Kr7Z8wyDjbOI39EDxejEFKihz6DOjP1TUpsWmDNFxJI36hVMG/8FbRB8aKO6ULopG+fFw5G9TPjOuZqYx95DMhjQxCWSd89cLDc+UqtQmsnVeC5fdoWNl77dz7qHxje6bVuyu9ws25vLyoP5FFTYmZn0Z8YNfu7k/RERcwgJmYbTWcLmLTNwuytRlGYsByJyPs4fw+ZN4OjThzjw7TL6zvOMU1ZVVfHf//6XlStXMmyYJyru3Lkz69atY/78+YwZMwbt9e/D/NEoh1cgDZl3TtpqXf4hhW+9SdQXvzSrKmF+aTVdfc7dPPKBUeH8GBTEa59+xj9vuxmDpnl5MU25um5LSQPC2LYjl//+ZzOyU0ECtF5azMEmQiItdOrkR6/4AEwNLJK29shGkv9rwzBcw99evITnn/sM1a6ja0zbBKVZ7jyCdOeuvHhDTqxz0iqyhj2GgfR0OtHqGh7q9B6cgCsjBVeFjfRpSVSlVtB1yTfoOnu6/3P+tRnZlEvY/81CbsKsH7lPErlP/hO34yGipg5vdHuPtvskv2rENK4aceZtRnYL456PF+FWZTLLzMwbHsgTl01Co2n8I31mdP15QePDe5F8QzJOt4vbn34MS6knKXzEVeH069H2hdHyF79P4PaHqLqy9cOOAJLBQMwz9+B1ya11PvN0sd0wdOtKxfvP4HPzoydvTyzKP+MxV2YUc89Xu7h3dk9ifM/dUIuqqty8YBtJcQE8flFPAi31/91qtWa0WjNjRu9Eks6vujEi+GgGS3QsXcJWsHeXF31rbtu/fz82m41Jk2ovq+1wOOjfv2YMOigeBT3K2rdQe85B0enRNbMYTnOt+XoBX49x4rv4UmK1PmhkLZKswaWqFDnLeeLq+sc++/bqwaHDh8jZv4mso3s4lpKGtwGm39G2i5Od7u9XXcG/v1vMI2/M55+3zMPrLL82rXXHzf1Ofq8oCpm5lRw5WkpWejnrlh1n+ecHURUVrU7GJ8hEZCcfho2MJjjAxOj44SSzkh69Y5AkiQf+72okSWqzaoMze87io7Xv8ciVT7XJ8ZqjMDWP7MNpqCpkHEsjIPTMQZCqqnyx5gtSCnQY5TDciopSUwDPUVMbRO1/HbtfvpS+936HVlt/YBr28se4UvaApCKHduXI0IEcm3kpPfYd8myg5KIL0ZH18M9A9elV7U5+MXb3xnfueI68+CG43ShhMZQ+cCdRU3c28dlrQHI1cdvWmzN0HAbtb8wZOgGToXU5SAdTSljxn53kx5vxSa2mOsxAn5DLmXRdAFl5eXSLPTu9tfp9H1EQdjURPfu02THNlzbcO+V/33Pk33tNreDjTJamFPB/3+/ljSv6MSo6oK2a2CQfrE9lfI8QbhrRtJLv51vgASL4aLaAUB0Z+aciYEXxzO1fsmQJkZG1xw8NhppoVWdCuupjtF9cyZJn7yTDHcnwoUPoM3s2zqoqDi1fTlifPvgGBCBpdcg6LZJGg3SGqz0Aa3EJWYcOYs3KYu2unciZB+mssSH36oH+SCnz39xFVWUWmWVpKG4Haw5+xSe56/lTUMO5J30uugWv9d+TvOYHYmJimTp9Bt9+8zUuuxWt4exE/kadln9cfgkLdibz6NvvMe/yOfQOb9oU1/YeupRlmZgIH2Ii6vYWFZRa2XOoiKMHi3nnv9tQXQo6TTE9xqhs+aCKY66fyLelkl2VS7ApiAmdLmFI7CWtas+o/hPYlrKFuz66hb+MuIfuXXq36njNseXX9ciSjJ+/H0FhwXQbdOar5YrqCrZv3s5vjkTuGGREliQ0soQsSzw+y/Ne6jv1JnbtWUh5aREBQQ0nRGo7nzqBBYyKpWRDGqqqeoI6BQLmTUPS6jwFzySVg2/tRS21YekbjLOoHGXzAdK+ugHtwKFE3HglpTv3E/TofU1+7hrZCyRbk7dvLT+zD9eNqT8Bt7n2bPYsUR8a7U3nMVFMHXjqcyy+U1ybPEZ9jNZUzHd8d9aO/3va8Bhc5TZUtxupkR7WtNJq7v10BwtuHsrQ8HO30Nyxgkr+u/wwSPDCnL6N79BC57rHuD4i+Ggml8OTja+4XMhaLT179sRgMJCens6YMWMa3E+K8nR1Th0fj3vYfXzyz3+Sk55OTm4uQX7+7N2xAys11U1V1fNVUVAlCX8vLyKiY4jp04ewPolotFp+e+NN9qWn0dnbG723DxddcSXvffsNPcclYNu+BcegHsgaDd6+MST4xnDlB/0Ybonjt8uW4eVz5noIXUdcTNcRpz7Y/Lx+IGv/JmL7j2uT17AhM+O7sGflCnJLSpscfHRkwX4mJgyJYsKQU6/33BfmM8ISSvmQPOxUMyRyPDH+vcgqO8TCA+/z/u7XKHda0cgyIUZ/XpjyHXIzpmhLksR9cx4m+ehOHlv7GF91WXQ2nlq9bC47I8eMIiShafU2rC4rer0eraxw89SGA2LdmHs5vuA2LLd/gN7sh9vlOuMCc5JfBG5res0UFAldlBd5z3yDz6REqo0GircfR8p14ap2s/3HTeg0BrqG6el2z/P49ogDIHREM6/GJT1IzRhv70CuuLonqRNj+WTBXkp3FpKZVcnNs7qf1ccsfvtmLJITuZELrLZmiI3AvmEJxlGe9Vzqm6H07o4M/rVwD2OHRp3TwGPxnmwWbsvkucsSCT8HQzxibZfzTNzQ7mw/UE3mqtXETJyAt7c3DzzwAPfeey+KojBy5EjKy8vZsGEDFouFG26oKYajq/lj8gpAbzZzw5NPsnfJEuIHDqTTyIarMiouF7nJyWTs3s2WJYsp/upLVBVknZarb7mFwC6eqqsvLHuBEnMJI0ZdjmbMVXWOk2SJ46g1H6ujmuZObkvs04cff/yRMVlHSLzo1mbuXQ9VxW0tx1qaR37GUUrSD2L08mLh3iLiB/RnYs+z+8HXnpwGDSNmXsLvh/TjAvoyotMVHMhbT6eAvhh1FmZ9lcSvh+czqfsdzf6g6N2lH5mrc3C73GhqhiuUkgLsGzbhSC9E9jEjG8Br1qVIZ1hRttHnY3Owd9UOHNV2MguycbmbNvTgcDr4fsP36Ev1yN5O+jyzgBfmDGRyfN2eml5DJrG9NJ/db1yPyV1Bb9sOdic9T98Z9f8tukuK8Io1olZXIFl8WRJsY7nRiC0ll78mZ2KO98V7bCgmbz2Tuo3gq3++gl/8UBJqAo+WUN12UM/dmjhtLS7YzKMPDOF/t6/EvjSL9GFRxJythRdVlYDshWT2epYo89ldYVq1VVP66kNUbdqCbDLiKqvCtmX1yeDj9yocLl5ZfZTVfx9HrG/bTANuivSiaj7emMaCeYMx6s59Paj2IIKPZgpNGoz/Z19xZGM1MRM9tz311FOEhITw7LPPkpKSgp+fHwMGDODhhx8+taO9AgUJx57vMA2/E43RSN/LLqv/QU4ja7VE9O9PRP8z1zC4YfgN/Hvvs9z9+WzCzEa0sg5Z0uBE5dbhj3Hr1DcY8e0UbvzhMn6cl9ys59x13DWE79hCYOf6uwEdNhtFafsoyzqCo7IYl60Ku62a8io7VrsTq1Opc30hyxpMBi3Bvmb8I7tit1UzJEKLb/onbP7wc8InPUxM5Jm77ds5WbtFHI7CM96fEHoqLPnHsCf57vDHfHN4IU+OnU+YT91CRr+3N3sl3+/4jPwiDRXaKvKLcgkPjcSVlkLem8dQ8cMcXoTW4oVqtVHwzFf4TIzGOLLhOjDu3Dwc+/ehlhWiulVUFzgry9mcU8hxvOgR1w2/0EBiAiMxBzaerHz7v28n2BZMxIAIfLv78sOM2fxvw27+vmgbWeNL2Z6ZxbbjlThdGnxMMo9NS2L8lLkwZS4Axw7vxfb1/awpLWT0NQ/VmvakKgrGnomUbThK5Wcv433L43wn6bhrdBKP7N5Ohq4I95FidGkZlOWn0Kn/EBS3i65JrRuecqs2JM7f4OOEKqOE2aby9ms7GHRRJ4b1CMLboOGtT/Zx4+UJSBoJf3Mrn6ckkRJ4Byb57HT9u9P24qqwo6QnU/Dqq1jGjCBiwU8oZYW4UpLRxp76XDmxsFxWpY27l+7jcFY580Z2anLgkV5UzdK9OciSZ6Vwzz9q8rhqPqMkCYkTK4ef+l7Cs8GBnHJyy2y8cHnfP0zgASL4aDZJlgn2r6ak9FR3oSRJ3H333dx9990N7+gTjrXzNMwpS8FRBfq2vaoI9g6ir1tlYv9bkGQVl9uO02Xj863f8eGihZTYS5iuC2W8XyNp9PWoyD4KGj0+YZ05tnUFhdnHKczPpay8AtXtQierBHob8QsKQW/xx8s3DD+zL90CQvDyD8XgE4imCbNY+tV8TU3fQ+7PT5GtNRA96SEiwxs+6XaENQqaQ5abvsbKwOjpDIyeztaMZdzzyw1EWyKI9+tC98BeOFWJnIpUcqqykRUHgSZ/1uZsx0fvTX9HPtdm3MqjujGob62iQFJwWv3RGwsJfuJG4FSgod++hfKl+3EXloHbjdels0BRcWzbROWqg6hOHbLRgT7SguQbgKTVIGslDpSkkKvmc/Ut9+AbGoMky/Sf3LTiZqNGjiJ5ezI9onowrmYo74mpE5nS4zhvrN9IQmgQ3/5pKsFmM/cv+Yp/L9+Au7qcI7k5ZBfnkV0uMXfGo5QseZeN/xhBWMJwdHojiqRFXvIzWL1w21RUh4Pv9yezJTyGp3Ye5vLj1eTYA/GVonBbjRj9enNw3WeYvP0J71p/DZGmUlU3F8LH6eg7Etn+0h7C853s++YYWWWHATAAC3ZtwGqS6XtlV2YMbFp9jIb4la9F7fNAG7QYKt9/gsoNW9DHRFO1fSeSwYTO14CqMRLx/iK0EZ6EWdnbD21U11r75jt0jP5wI+Xldq4ZHMNXc/qjacbswE3Hi3ArKv1j/XGrKorCaauH12RWqJ4ci5oR9Vqri4PKjMRwBsWd24TWDpDycQG8W9pBUISBIztCcFVXo/VqetecacKDKMd/pnrhnVjmftimbco7uIlAXzPhPWfWun3kDiOphQ5CHDFUZUznKDCl6WU/ACjPSyOtDH5Z8BxhAd4EhYYTP2IUvrGJyOa2f9PExfQhbt5nHE/dQfbSx0gz+BA78UEiw9q3cFZbqK8AUGOSoqfyWcR4Ugo3sa9gO5tzNqKXINwcybCIEaiykZzKbP46eBZ9wsew68fBxDx8E9Xf/4Bp1BDkoHCUKitKad1eF/3Awfj5eOM4eAR3SRmFT30Kkoo+WMX32qloI+tfF8hocuNa9xurvnwdhyIx45o7MId1btLzmTtiLi8VvITDVTtHYlhcJ4bFebL7k7N+YvWul7mi51yWVixh1f4iekV0o1P3XhRUVPDC8kPcMXA7aZlxlFUdwlc5gmNfLGnOG8DPj+uvug0KX+evHw9jdtJqhlX1Qva34PTXI8sl3HDHFZTmVbFxkZ24xDZY+0hVOT/74mob2j2IA5dEk7WnCK8MK6WdvZh2ZTz9ov2wuRQWLD5CRmYltLKKvzT7LTTfzoMxrVtWwJ2TQtHCJYQ98yKO/duIuOufaAKakS92pJJ7bhrIpd1CWpQD4XAp9Az3YUjn9p/efr4RwUcLhPXuhLrDxvGfV9Bt9szGd6ghR/anuv8taJO/OJkM11bK8jLx1dc9XvLmQCZNKufQjiq6xBxm5D1XQfYuqMwDRQFLEFjCwCeiwbVnIvtP4L7+rV+Hpbk6xQ2g05++JCVlK9lLHiNT70XMxAcJD+9BpbWS/nk/4h00FQg752071zQaPd1CR9Mt9MwLtQFIGjeSLGOefcnJ22SzCdlc/5L02m4JaLt5uqKbGholDptI4jDPuGP27pV8veB/DOjTm15TbkBuwpWj1MiJOqdwHeX2EjIKljMlaQJjut9Z6/4S6xru/u3fDAjZxchYN0lB11D19sc4e3RmlLkau+LLFimEgNBPCT0WjGIsweUupLS8GkdBBe/fm8y8l55i2u0tryp7OlVVkDj/pjvW56ap3WBq3UDfSy8TF+NDyruH+N9PWVSZNTjNGh56YniTfuen8+vRm2K3jLu6Co1Xy3qByxd9Ss4TTxP15P0Y+o/G0L/x98bv+TttXBbf8uR2p1tB14aF1/5IRPDRAqGDkgj/9nO2rdLRrZmBu6nbKKQdb0F5Fvi23Sqc27dtqncsNj74MHvXygw2LSDKfQTefAkM3p5/AE4rOKvAVg5eATD9RYgdAbpzuwT7mXTunETnzl+Qcngd2UseJcvtwuC2MsmlxWzrxakBGwEA97mddRHRdzzX9BjG1s//zWcv/p1pc64jsFNio/upUsN9v17GMIICRnHZoBfrvX/mgBhe+m0fe/P7cWe/u1nx23UYe/diiE6Pl8bE1i7z+DPfEGpLZUT/K5g02PNGLcsv5tNH/onVXt2yJ9vQc0Gho/Z8FCjmNptaOaFvGCl46qeYq9xQ5Wb7oSKSEpq5SrWqYHLntDjwANAYtRiCvfCa2vKF6XZpW9dj4XAp6LUi+GgJEXy0gKzX0bWXgfWb/U9OuW0qKXowAM6936MbcWcjWzed3aky/rq/1bl9/P9dgSN9P6bSq6HPlWA5w4fEprfgl8egMh9UBSwhcPkCCG480fFc6Bw/EuJHUlFRhLclgFUf/wvv9l4XuiOylZzzh9QZTAy/8Qlidv/Gb9+8z5wHXjrj9hINLzyXlf8r9qyXUUxDT9Xq+J3h24rQm7UsrjJRnjkGrbsaqTqTh4a9QVJYEnd1mUzs6pW8NOMNusX2xmWzk7klmYNrNuDtG8p1L9RdPqC6oJqUNVno9Bq6z/QMIRUdKeXAz6nkZ1YSGGQitl8wUcPC0ZprTxFVVQXOUaGn7NRkHPbKkzkDqqrUDPuop25DPXnb4fIAPkzOQStpUFQVXVYavTRWJL0eyW5HKiwEvR7VYEAyGFD1+tN6ZT1fT/0o0esSGacbKuwKOcshMDefbJ0OTraH0+u3eUoHnGj8ifuythAtl8HR31U3rfO7lhq83xCkwZpZRfni79BGNW3I7/d6OYvYlFJU76P9/u/u9B9PfHs0v5LBnc5xvsYFQgQfLVRVasWo0TerdDkAlhAqw4aiW/UfGDAXTH5t0yBZJmXTEnpMvK7WzRpLAKaeI4GGp/OeNPR2z78Tdn4K703y9JL0uQIG3QzmYNCe27n5v+ftfepq5XxLOK1yyPyyex0BFh8Gdmm7yo61mNtvqfWijKN06dq0E0FDV+ORIRMpTZjPP/Yc4IO1X+Oj1RBv0tDbNwSr286WcjsT/KysGxXNwfhAntp5Ne8lv8HcsUfpW2Sh+lge9+//GqPGgDbTRlbBXr558R9EhncnfvA4ctba+P6RDUR29SVuWDh7f0ihqMiGTi8TE+9H9qESdq7JolNXXw7uLWbkJZ0Z+qde5B0oJnVzHjtWZKCVwGjRkZ9XzZTbEkGvYHPsZdPKFz2LzCEBcs1qt5JnVoUqofK7qcgnTtLq72847Yta+5Wqdi3CrJ/EqVOgfPLbmrkUNSdOz43dd3dmg1OLRiNTtPcAw/YsRC4txuByY5p5FfbAICS7C7miCtnhQHac1nOmqnW+nnhUn9Tj6NMMZP6aiGW0pXYbpFMna+l3Z21JAu/KClxD70FbdKzui/H7x27o/tJKgm+9AXeVE/ehQ7TEjX2CSc4sqzn6qeP//qFP//H0+7qHeZMQfu6Wo2hTYm2X81NejkSwT2nzgw/ActW78HJvKhbeiff1n7ZJe6bOnM1vP31P/Dg3cjPXR2lQ/7mefyWp8OkVsOcrcNk5+Vb0iYCY4TD4Fgjs0vrHU1VUtxNJe2r4yOZwcXjXOpw5yWgCu1B+ZD1+eZtRJJnh1h3si3mn9Y97Ds3q48fOtAxWHrKy7G9nJ/gwyQHsXnoiI/DEJ6VU872EjUr69H8fU3jzZz41JqrHIFZ8/yk7nrmPPz383wa3ayjn46Hdv/BhoZkwqYoibSLpo8dSYitjV9ERkkuycKoyd0SFEGDqyYPHHdx6qJQ3+0Sg+t3A8y8+T8S8W4lMGIwtO589zzxPurodt9tF0shLGHanJzDvMcPOrq+OsHlzHru35jFkQjSj7huApqb7XFVV9i86xrHNuXTp7k+XCZ6ZMJEDQokc4MkPsFY4sOVW8dt7+/CJ9sbP0Adr5Z01uVwqSAqnXnsV8PwsSZpal9Anp2LWeTl+fwI/dY/FZzIhEU2fGuy3cSXvTO+NXqfhiZ8/4NZX38Kikfnkjhu54q7bmp2vAVC2eAkFy5cSu+BDdOHhje9QRzRweQv2O0ULBE1t1SFa2QKhNUTw0QSuqkr2fv4DmSl27HYNVqeBMkc0o4cWtOyAftFUxExAn7Eeqos9uRatZAmMJKtSwm2vQvZq40jcPw7u2lL7NpcTjv0KB36A9yaDXwx0HgPD7gJzUJMOq7hc7Nm6ioiYLqj2Sqo+mYtb0lEYPASX04mlOh2tpOAM6A5hfXEeXU1AbH96X/8kaLTc8u4aRukiOXMFlI7ltkmXArD1tXfP2mPET/31jPcfXXExbvuZV4ptqcCu/bni/v58/sL9jW5bX8/HLZ3781PRev4cE84tXT1DlP5GX8ZFDmJcZO0qqJ/0hV4fj+Dx9HLCAkbTe1h3zMtfJfAzK1FFEJ+vp++Dt9V5DJ23Ad8oC6GHS4np5kfP2V1qnYAlSaLXpV3pdWnXOvueYPLWU51Zgcmsw1CzunH3fhMbfc7t6ctPv8YnrjuBwZ73Z7f4niz9y21MfeFVtKbmVdSsWr+eoD/f0cLAQxBE8NGo8mNH+OrFA9iVMGL80/DzcxFicBPWrYquFzczbna7oPAQ9iMrkMpSMDhL+OWjx5h0+/9a3c51P37CVdNGomsg8Kgoz0dBxtenaYFBo7Q66D7N809RYPfncPQXeH0QhPeDKz+BRha8croc9Pv5MjYHzEJblY/bN5GEG19DyjyOv5eWgJieSJqGh3hcGiOq9McpytNmJKnestJtyeWG3YvfPvmzp6v61OW7PSsPKaTuFNfO3kGsHDGR4evWcH0nJ4Yz/P4BXp4wn9W5e7HovKl0VvBbp7Hc6u1HWIAJo63hv434KXHET4lr5rOqbd+SVHpObF19kHMp68cF/PmjU+X2Rz3xNC9fPYvSG6/i2i+/b9axKtesIfyZs7fYpHB2dYThahF8NKI8PQu74jmJ6vXQb9YAAvv2q72RqpK15FEqbZUE+wShNZhx2qtwaQyoWiNy4SE0mVvwqszB5KxAkvWURwxBSbqZVakBuJP3MzWxZ5Pak1lUxK9HjnPdkIFoTuuLzS8uJXLAlFrbKi47qRn7KNgwH6m6kMji/ezudgmjL322Va9JHbJ8aohGccPbY2DPF5B08xl3K6+y4pAjGHLXAs8xanj7Nr0nqNXLtrejhpIpz/rjIp31T58x4ydSXpgN1B7zP/GdRZuCD/VfNadUFqHHga6RNW3cdjvHd+fzr2k1ywkkwt+WJPO9W0GTr9LP4sUjrX4mdamqyvbPDlJWZidmyPkzzdsR04eNm3YwfoynGNz8K2dh1shMfviJZh/La+BAHMePY+jcskRPof21d6q+CD4aETVuLNd2Sidl+Vr2Jpv56s18rrhrL4G9e1OyYT629C1oXVYijy4BoMIUjNZlQ9Ia8XI70Lpt2PU+VHSdiuwfjTFuKProwUTUrPXy58QKXvroY6KDAugV3vAH2b7cPL789TeqrFa8LRaezs/n8VmeGgXluccxSzYkjY6qymKy8lMoPbIa05GfKAvpQ9DAufToMZqi4iwCPrnm7L5gsgb8YsFeecbNVLcLr9d6Uj7lnVqBR3O095unVRQ3h1e/hZesIKmguhUkVUVVVCRFRVGcuN3VqIoDNBqQ5JpEPqmm50IiqNsMLF1aMOgkcdaDj5ikaWe8f/vSLWiNtXs1Cux2Ejfsx0/J4/3EvsgNzB6ptlr5/uffeNUhczw4jNml5QT7eXr8np/hmeLrsLvo/9sebiqqIiKwbasJ7/nqMBWZlcz4xxAk+fz5K7z+r39h/n9fZ/yYIdjLynCjMvm6mwnp2/y/Ia+BA3Dl5YngQ2ixZgUfb775Jm+++SapqakA9OrVi8cff5xp0zwfNDfeeCMLFiyotc+QIUPYtGlT27S2nfjGxdDl4lmkH/2CcmcQ1oJ8ADRrXyDcmk9eSH/yQvrzSPx9TOg1gqvDa88d1wENDUBE+npz0+Vz+ODb7+iX2Ju5I4fVulJcl5HNj7+tQnI6mTp2DGO7xKGqKv9auIiXfl7JvVPGs3LrWkLsh9g5fxYOvQXFJwptRD/ib/8Jw2kzU7y9fMhyVFNht+FtMLb1y3SK1oijNAu9qoKqkJu6H5PZB5+gSCSN508uO/0Y5fpuJAyrf4Gnpjpf+z0CyyUyDh8kJhDQSCcWfqj5CpKkQ6MzgFuHpNXWrHRcM6VScVNdnUrlhv/Qu8vnLXh0CUlV2vopNYusulGk2h8/gTodk815LK8Kw6bUv0BdWk4eQw7mgG8E/TKOc9eBnZgH1k12fm79Ua43Wdo88Cg6XMy+jbnMeWY4svb8GvKLjAxHY6+iotqGl8WMWasjYmTDK3GfiW3/AbynnTnAFIQzaVbwERUVxXPPPUfXrp5ErAULFnDxxRezc+dOevXqBcDUqVP54IMPTu6j15//iy0VZlfy+b+34eP0ZZLvfwlev43KjQYsjjIKh9xN6LSnAPhLRRU37DleJ/hoTK+wEJ68+Ub++eW3/ODjw8V9e7M2PYsfVq/F4LRzzcQJ9I05VZBMkiQemXMJ//jsK15fsZrcApXLbv6M/mGNFPrR6OlTeZiNS/9J18FzCY7s1ezXoimKrC4C977Nrn3JqECVORqNy4rJXoiEgk02Y7Llo7n45VY9zvkaeAD4uk3EJd1O1/5nXjyvIcUHV5Cx/c0W7auemPjSnhQ3qlz740eWZT4aPJUZX33B3oAwRgfF4Sorwxh46v306eZd4BvKrWW5/PP6hiv8xQea+SGzuM2b7RNpISzawqLHN9J/Ukyr80bOhaM2O2+uTuGS/pH4xnRh2fI1zBw1kCLVTXnKMYwDGq+VrjgcyKd9lrsKC9GFtN+UbqGVOsBwdbOCj5kza5cSf/rpp3nzzTfZtGnTyeDDYDAQFnb+jIM2xWffHsJt1HDV42Nx7cvC4R6DLEk4ZQ1Biac+APt6m/HXaVmYW8zlYc2bwWLW6xnSuxerli9n7YYNGIwm5o4bQ7+4+hPaZFnmH1dfzj/eX4AuK51+oY0nkup1Bgrv3oc5Yy+pix/lQORgEsf8BX/v2v0ytupK8tIPU1FWjJeXGaPFn/Q9q0gcewXmJuRjZPoM5MigsQy96KZ673dXl6JKMlpT62bltEe+RFtxIaFrVU2qVjx3ScIz9bP9/Fa4i+5d6l45b7jzGqKD+pJWoRJVvLfm1gy+9oY5FeArm0jITuftiBgetTvQG+q/uLFb3XRt4L7W0Jn1jL9/INW5Vfz00k66Topp0VTVc6lSUXh5xRFKqh1kG7vgvWEZX/76JQA7PvmAqQ0EH+6KCko+/YzqHdupWrMWY69eaAIC0Pj7YUxs3SrAQgfQzp+fLc75cLvdLFy4kKqqKoYNG3by9lWrVhESEoKfnx9jxozh6aefJuQMEbLdbsdut5/8uby8vKVNOmvMGplKSULnH4xh9L1n3PbF7tH8aW9qs4MPgEv69uKixJ7om9idq9VoePTG69hwPK3JJ+KggCh8fSO4OzOc2KwP6fLKYPZ6D2bUX95j1/ql5B/awuTMVykwj0UN7UmFrRqpqgB7QDcy/3cRcQ/8hkF/5tLrbkmLfIbS2Rovvya19UJWdvgoOm3TVoGtjyf/o/lXL6qq1pSiaN8rn1LcdA2oWznXf8VO5vruxf7iO9zXIwZZUei/L5M5FZ77y7x9cBiM5I7rV2u/3yfvGrQyWx12Xlp9mOk9w+ke3PwF/c7EK8xMl96BLHpoA2FRFkb8pV+j+7SXN+KimTivJ2racdxRoWTcugb74EHsQmZfViraB+5m4guvAlC+bBkln32Ou7wcfXQ0PjOm43/N1Wh8PBcKrsJCFKsVfXT96wQJQlM1O/hITk5m2LBh2Gw2LBYLixYtomdPz0yNadOmcfnllxMbG8vx48d57LHHGD9+PNu3b8dgqP+E9eyzz/Lkk0+27lmcZdMmxrHoxZ3kHC0lMt7/jNsO8DXjrZVZlFfM7NDmBSCyLKNv5kWUSadjQnzD9Qh+74uDOTy6eD8heh2H3Jfw4EMvcuTLF9j77/EYFCcJ4+9lb8LnDBw2tU4Btb0/x7DjlWuwTHqQnr36o9HVf2VZUlpGly5tNKW3A9qYXYLdferkXVNTsvbPtatTn7adR3lcNzIys6mwViJpNUgaLXqtjF6rQ6/TotdqMYeHnbFgnKI4G50xU5mdzP5f/4wiOVG0LmS3BreznAhbPrTjIsETggeQlbsTv7C+tW7XfPwKmjvuwZn2C0W6PLrE9OV4UmcKrU4yDx1hYVo23wVFUmm3YzEYmPrDLxS4Qed0MMCsZ0JECJMTenDVoBhGlATxwtbjvLgrnbcntf0QY7/rEuicWcHad/e1+bHbkiRJVHzzNflPPomxVy9CH/o7PtOnE/bWfAgOwjxh/MltdWFhuCsqwO3GMnYsxh49TgYeANqgC/d9/UfS/oMuIKnNnKvocDhIT0+ntLSUb775hnfffZfVq1efDEBOl5OTQ2xsLF988QWXXnppvcerr+cjOjqasrIyfHw6Rtnawzvz+WX+Xq58NImgqMavoLaWVXHbvlR2DD87ORX1sbvc6GQZ+QzZ94+vOsx3O7N4b+5Adh0q5OklB/jnxb0Y1jmQnNJq4gKMbM0op7DSgbdBS58oX3pH+tU6RmbyGvI3foZako4WF4rWRHXEMPw79Seu12C8vP3Z/OIcEue9hpf/2S1ANO/DrYzqFsRNIzo1aftfU4v42w97G+5tbMKq6A6nGwmJmFDzyV3qvJNrV8g+7ebTyjdbrfQMsnnWQVUUFFXFpYIDcAFLgiN5V6riorH1VyF1lOaz59urcOmrPEkcpwqYnuTUVSA5ZRIHvYlvj1Pl9Y/eMw+j/RDa7nH1trvOTY19RPzu+SpuG0bHHlRvCb1JW+9xf1acfBPgj8FQt7iVerCMyEwXfpUqAzW+hDndJH68hbJjR5n7wzLkyFhssoxNqydPZ+TgtBEgSby3eRtHi0rYbFfoARgMESzTuXkyIJArBzW/HoeiKKTvO05cYsPVe/d/f4ysQyVMenBQg9u0t5/mJzN2ig+F//kP+rg43KWlKNZqHMdT8Z15EfbDh4n4979Pbq+qKs6sLGx795H3n38T+eKLePU/n0r5CY354P/W0Xt0JEkzmvbZ2VTl5eX4+vo26fzd7J4PvV5/MuF00KBBbN26lVdeeYX58+fX2TY8PJzY2FiOHDnS4PEMBkODvSIdRWmJDQCfoKZVAUzyNWPWyPyYX8LMkDP3lLSGW1E4Umrl0V8PciSnAlQwm7TcPboLVyWcOvFXOV1c9+0uMgqrWX/nSLz1OpJCfJicEMqtH2/jtZVH0WtkJCDS34SvSUe5zcmLyw+z/bFJtR4zKnE0UYmnlq4uLSkme+dPlB1azYG1r6FV7PSx7sbo2/JlqpuuefH7nvxyRnYP5rUpTaup0p7mf/kd7piGu7b1fiEMmrfyjMdw2irA6UDnXTsB2p04i7zkvcTPqcnJOW3RMOp8e9rCYnXW+Kpnewk2rLsct8aXwSOW4BtYf/7XFTX/mmLfXE8A9u7Df+XVubfQeZYn96zCaiO7vPxkD93NQ5NO7vPlbzvZdczKL+Njie7cshw0Z6WdD7/5mD9bbiWkk6cgmsvhpiK9AluVE72Xlv3rsxl+ZcdYePFM9NHRRL9RfzHD7P/7P1wlJWj9PZ9VkiShj4pCHxWF18ABZD3wN3wumoGpTx+M3bufy2YLF7BW1/lQVbVWz8XpioqKyMjIIPw8L8HbOT6ArUB+ajlRPZo2lPKf+Cj+ciD9rAUfG7NLueWLHVTmW7l2Wje+vsKTNLa3oIJZ/1vPq2HH8DFqsSsqOQVVdI/2ZcufR9U6YcQGmfn53vqn2v28L5dnlh5otB1+/gH4jZ978mfF7aaiOAdTB0zCszsVDOfJ8tcuWYOmldNhdUZvqGdGddSMURxYsgTv6MhWHb8+brcLfLNJiPoRvwYCj9NVllZxYPNOzIEgc9rv5rTgp0r2BE8jBwzj54/mc/3QoZhDQvE2Gemm16G4665ndOW4/iQe+InSRblE339xi56L3ttIkOzDog+WoxbGEOKjR5LAy6xDr9dgs7oYe0MCQb3O76EI8/Dh5Pz9IUyDBqKPjUUbHIw2OARtcBDa4GCi3/gfFb/+SuqVVxG74ENMffs2flBBaESzgo+HH36YadOmER0dTUVFBV988QWrVq1i2bJlVFZW8sQTT3DZZZcRHh5OamoqDz/8MEFBQcye3fCUuPNBaV4V0PSeD4Bh/t4YZJmlBaVMD/Zr0/bcs3w/S9an89ltQxkcUfvYvYO9Ofr4ZHKrHRyvsGHRyPQJ9m72zJB7v9zFC5c3f+EzWaPBNziq8Q3bRPOek93tRqc9P2bISLLkKVt/FpjDA6HqzEXgWqKirJiN66cgafVIWkfjOwC5qcfY9mMVCWMrUFEAqc4wTr7pMgYDQ/7vEYK+Xcgnf55HiH8g+cWFVNYEk539gpg9/8Nax+501UhyntvE8f/7lZAHBmIObt6FgCRJWAxm5vz1Cr56aS1ylIZZN43q8LNbmsv34osxjxqF49gxHOkZVKccx5Wfj6uwELVmhdvKVavQxcagCWxeGQGhg+oASR/NCj7y8vK47rrryMnJwdfXlz59+rBs2TImTZqE1WolOTmZjz76iNLSUsLDwxk3bhxffvkl3t5tm2l+rmn1nqsqp8PdrP3+HR/FvYcyWhR8/GfLcT5Zn4pep2FUzxASAsxkllrZkl7Csaxydj0yEYu+/l+fLMtEWIxEWFpeSGxs92C2pBQzPbHu+hsdSXPeQzangtF4fhT1lSUZxX32psNKfgGUH8vEp0vbBIr52QfZufXvKEooEyetRadr2t+ewSwTO7CIsXMarrz79YpPTn7f5dLLkYxe/Pj+/4gJCmXM1OlI1Va6XX1tnf0ylmzFSzZSKhei82rZe8GoNYDbzY2PTeK7d9bx4T+Xc+ldI/ELOvO6RecbbUAA2oAAvJKS6r1fdblAozmvp7cLHUuzPonfe++9Bu8zmUz8/PPPrW5QR7RzTz6KWYN/WPOqJY4M8EYrwfKCMiYH+za6/WtbU1mwOR2ny02wv4m1d4ykxOFiwc5MNqUX428xMLhTALGBXg0GHm1l9eECFt42/Kw+Rms192PQ6nQT4N2x84tO6BoaxP+OZfLRp54Fv05MjT3xnB2KynhfL+6+eEoDRzgzn/FjOXLjHfjfdgedr53eqrZWV5Wy58BF9B+4nJCos19u22D2Isa3hL6+WXSe/UHDG+6xUmwqIfHJS1t80vT386cgLZdO/bpx6W2j2bnxAF+9uI5bnpnyhzoRS9rzI2gXzh/iL6oJdDoZ1aVSXmjFL8SrWfs+Gx/Fg4cyGw0+/rbmMD9szWDZLcOJsRjQ1HTt+hp1/GPMuZ0TWWlzIksSKw/m0TOiY8w4alAzuj6qXQreuvOjJPbEEYOZOGJwg/enJO/jlUNpLT5+t9sv54hWgy0zp8XHOEFx25EkFS/fs9MbYHJmYlv+AW67G9lVhl/2AWZH729we2txGUe+WoXOR0PPBy5qVZAQEBRAUWY+nfp53oP9hyVwdFcOyz7bxLS5wxrZWxCEhlxYg5dnyZiJccgmLR8/sYmP39hFXmrTC6GNDfBBAlYWlTW4zW8ZxfyyPYttd46mk4/pZODRXpbtyyXU28hd49uxEMRZsL+8GmtHGOxsA2ZvC9WtHZZpo5di/17PKsm2SmvbHPA0qqoyLPwL3KteQ921CNfBTcjhvSgOmkmm//h690lbvJWA1ACkEB1aU+t6ugIjQyguLKp12yU3jyY3pZyv31zVqmMLQnvpCJ+CIvhoAu8AI7f8Yyj9ZnWiLLOShf/expqfjzdp33J7GWONaTy6f0eD2/zfj3tZMHcQ3r9b5bO9xAWaSS2qoriyaUmD7UltxtsoRKfl3RXHGPbm2rPYonPD7O2NTekIHyGQNOwl9I557EyeSvrh7c3ad93hI+SU1x8gOGwOFv37LSrRYn5mB5bHluD90EJMl96Lc9j1yNSfg9Xj+omEPpaEK9fK/peXNPv5nC44JpSS0pJat+l0Wm58dDJFaTb270hp1fEFob2096ihGHZpIoNJy6ipnRgxKZalXxxiz3fH6dEjkJDYhoclnti9mI1lbiYF6LmSrzhcFEF8YO158puzSykusdE3pOMk5f6yP4/OwWb8vC6sP49vLuuPLMsMfH01LreCVnP+xt5e3hZsrZ0N00h11KaSJInwqOGk5b/P8aPfEBM/EMXtonj7j5Rmb6DCegAruXTt9iAhg66gZO9KUne/zF7ZyCcHr2aiJQK3W0FC5cC63eSlprN/zTIUt0rnzmEE6ovqPKZ3TAKl1Q0vHKczG5H8dZiyWrd6sznIB6vdVu9zvvSvg/n21U0c25PF1GuGoTvLeViCcCER75ZmkjUy06/uwf92pPHil6s4NNxzAqivyKW/bGfpiEvRaHQkF0Sz4chrxAe+Xvt4Erjt7kbLZJ9LXUMsfLQxlZwyG5H+zctxOZea+3KdmCKpN2qZvGAzK+edH2P22zZ+hrT3GwBUSUZRFJYzgIMRoxvZszESBdsOcOjZ9UgmL1RFRVHUk1/t1S6CoixMvTWx0SPF9RjJsaND0ZoN/LDkEvxT96LLknBX+GB3BxA+63aO73uFlIMv4jBVgXwD3+zz4dGLB7Pm88O8fM2smiYZkSQNvcddzuRb5+AqL0D735dJf+XSmqnHKkgyKG5cRVl8+tfriQ01IskykiwhSSe+aojMm4MhJofyD78GGcxj+6KJad5QoizLDfatBYcFMO/Jyfy6cCvvPrqc0C5mvLwNdO4dQXyf5ldUFYQ/EhF8tIAsSwwZH4m8OI+/XjaA8C6NFx5LDO7NtiMOjpYcpau/p0Jsud3Jn77YyWs3DuowgQfA5YOiOZxXweSX1rDvn1PbuzltbtWNwxj6xvkz9GJP30LYxEcIj0hAQsW68ku0S38hfmcsXy9OQ1LdRHcyMfjvTa0Z6hEyfjBbVxURF6TilxCCrJWRNVLNP0+p/p/eSm7SsVKyMjm2/HoMoYcInDKW4OA7kId4knuP//YjOceOM/7O9Z6fjx3nom8OcNGQCIb3D8di0mEt/Re/fPw2/5j/Rq3jan2CKb92BT41a+AAqIqCqihkZ+SQu+BTJl//V1S3C1Vx19znRlXcuKuy8fEPQ1JVbPuyKFq1E2sfiajETrgq7axbuILUwgykmv95GUwkJibSc+KAWm3QaTTYq2wYzHV7UXQ6LdOuGYZ9toPdm45grbSxcfF+Nnx/kCvuHY2qqnzz+lqiEwIYMbUv+g4ytCr8wbXzwpIggo8WGzS1Fym7cvnhtS1MvLEvnfuGNRpADOx6J6sPvkpyyKPkldlYtCebK4bEcFHn4HPU6qZ7ZEZPPt+SwdBnVrDi/jGYDR3wT+UM759dew9TVVENgIKCv68vvXt61ugwaOV2H+9sDr2zEp1XAF4166BUBXYhtM9hBtxyLaqq4iitZMmjP3L63JhVTy0iP8uKrLoxeOmI7OpDcM9IDH5mSo5kc/C34zhULYOvTKTrxUPrfVyXw43R0vjJMqcwn2/e3kjileFcNOZuVJcLt9OBotYECcmbUSorUVWV99duYXFaDp9fMZC53x7FN+A4D4/oAoSw/Mv6h0h8utZeN8Vls7L30/9wZPtWLrpiGsEDJtW73+mKK7/n2w2HCSt3seynn5BVmaTBSYybN+Nkj1hpXjGrF/3Clm1bGTt5HNF9ulBwLJsSa3mjhcUMJj2Dx3nWchozE1Ys2sJH/1yJ262QOC6C/PQK3n/8VwZMjWHw+HO35pMgNKx9PwQ74Bnl/CBrZC7561gWv7GGZW8dIKL7ASbPG4HZt+Hs+j4hfVnySw5L9m3AP7wL/WL9eWTY2a+L0FJ7n5xC0r9+wdVBEhvr1UDTvnvxWby798dps2I/vheXrKf3Bw3XqenI9C4rquFUjZn8YjNeKVvIe2YKoQ//jN5iRLVW8/Xtp4px2RwSFz0yDt/O4ZQdOE762kMc+3UfDoeK2VfP6Psn49/1zMseuJyKp9JqPd7/9XOqD2twqwpVGQp+fWR+qUpm/rvv8p8XdpAR74/d24AkSchWO8a5t3HNl0vob6vkqzkXobNY+HZeIJOe+41As57b+p15ifbK1GQ2vfssZaUVyBqZ7n17c9nLXyPrm5bToVhcJHTRMG7uNZTmFeMd4INGV/vjzy80gItvv5LKwnJ+XPANSxYvIdDgx9TJU9CZ6l/BuSHjL0kiYUAhoZEBaGp6bPKzi1nywSbS9hUy7vK+BIX5NeuYgnAhEcFHKxjNOi57YDzHdmbz2yfJfPL4Kjr3t9B7VC/Cu/jVu8/0YQ+y+uttFBT5cESSGLctG0k6tSS7063gdCu4FBWHS2HpPaOIase8C0mS2HCskGm9O+D6PGcK3C3+9Bo4gG0rfkUKjmbUtBnnrFltzaE1IjtPTWPtOXUgTF1B3jPTAJB0Oi57/+YG9/fr2Rm/nqeC3F2H93OoOg9pTz6SJHHkeBqXTp6EyVj7RO60uxpcJbnKUY28pxNawKx1kLs7l+291vL46AfJL96Ma/VaXN6dmf3Ws7yzcQcvFVTwVacAevc/lT9irDn28XIriqpSXW3li8+/w6DT4lbBLWvR6Q1Yjv1CxdG9jJr3V0IG1D+9tjGKoiLXdHf5hZ55mNQS5MNV992Iy+ZsdtBxgiRJRMTW7tEMiQjg+r9PYf2yXXzzygY6Dwhi0uUN13IRhAuZCD5aSZIkug6IJLJbMJsX7+Lo9mIOb9pBrp8dV1wxhRor5XZQlFMf4g7Vwhe3DcWtgNut4FZV3AqgqliMOryNGnxMer7ensH0V9by3yv6MbHnuVgltq4F85K45aPtPPxtMirQJcjCN3/uIJVPy4vYuGgF2d+XeyqAqgqSqoDqSZjcvuo33NlHUf1C2fzzz2z++WdOdJUMLy3nPx8e92StynL9y7b+zulDNV2LLAQZIqgI8ASG0u+6YCSNzMSLezQ4oya/ys725ceQ3b9byKSmFXqnDV9W4vBzEpK3E5x1Z1w0p9v0pR/fJsAdjMuhkL/ViU/8iXapOHf68GX1cvz8LGhkGVmSkTUyrkpwyPVPt/7L9D+hTlM58Nk37NpQRZluD0+Peowxsb0pusYP//tuZ1PSCDIOHUc1GBhZksIbpYW8cVrwUe5w4xVo5IulR/i/IZ1YZxlAULEVX6MGrUbCZbehuFzo0tYz++VfkbUtz5dQVc+vuakkSWpx4HEmGo2G0TMGotcns+2HLDL2Lzvj9iUlJfTs2ROd7rTn/vvVhevb8bQbCzMq2rmDXRDqEsFHGzF56xl79WBGXaHw/usbCDqkohyN4O6HexHkE4CuBeWJ5wyMpleEL9e8s4mrB8fw4NQeZ6HlZ5YQ7su6/xvvuXKUJSa8uIqhz6zgw3lJ9Ahr3+qnETobPcaNYNKIPp5l1SUZZBlJkjHpNShOJ+UVnkUBT+TjyBJIkkx6fi5WW7UnQVFVUBscWlJP++8pxvQMTL4OAvvGnXbrqY/4nKUprFh8GPm0hexOz/Gy51ejkyXCh0Wc3O9EG1VVJWjJ90iygbzEfpSFJ9Ir+PTHOdGypg+H5a9V6DohAJ2vhon3xREbfmpNlx0H93Hg8HEq7J68DEVRUBQFm9POJq8VBL2QgiRJjLp6FgERp67mJUmiMjsbN8Fcr19OzqIsXOW/cESfhNY7DquXNwFhwdzqa+HWAb24acE3pGZmExflWS9oydF8vL10TO0fgb9BhyM4jgfvrJu/sfXFH9n62ZN0n/lX/PxbtoKsoqonexc7gsETetFjYJynRTXNUlW1zh/aK6+8QoHOzZVXXlmzTRMO/rttpJoEYkGoRdT5uLBoNDK33DOSzCMlfPfiTvavKmPCpSEtPl5CuA9rHxzH3Hc3M+CpX7h9TGduHd2lDVvcNCe631fcP5af9+Zy5fxNjIkP5oXL+6Jvp2XqFRUsFhPBAQ2UrtdrsZjrX4k4pJkrnP7egb3leIXqiI2vP1nYaNJRVFBV+8bT3+yR3sTG+hESUP+Qmu2ghKMwiH6JDSdTNudk6mvxZuaUMfXeN6BHLwb0qJsEWVSez9oPPyIuoTfJK1dxfPfhWsEHgHeoP8PjzURN245vUQ6V2pcZEhTG6s9fwNu4jV2LlzNi7qUAaFH5bHcKwxUDt3+6A1uZg6dv6M/0Tp5jVjewcOPAvy5k1y+fkv7udRzGAN0mkzTrNiS56aXylWb2fJxtsizjF3Dm2j779u1Dld1MmDwOg5eYJSNcWETwcZZEdfMnrKc/B5dnkDQmCp/A+k+CTWEx6vj+rpHkldu4+H/r2XSsmLeuG4Be2z7rlEzpHcaY+GBGPb+SH3dnc9nAtlkZtblK7J5gr/00fPLvHO1L5+jGFxNsiBwWD8XZZ350nZ78pyehnfEvAvoNOXm7zW4no8CzZkuX8JhaV72KovDUPbNx6yT+/vQneJlOrcdid9nYemANWXmppJccZ2dZMp0CO9Fv0lAy9h2s97Jb0ptA1qHVG/APjzt5+9hr/sbqikJCP36EtE+ewe/iGYzM7sw/DpTxzcE9XD+2C3MSwoj3OxV8VTvc3Pnpdv43d2Dt10KjYcDU62Hq9VSW5LNzyTvsevNG+t/5cdNeTDw9Hx0o9jijjRs3sm3bNoqKirj++uuJjIxs7yYJQpsTwcdZJBs8wcGeDdmMnNn63opQHyMr7x/D7R9v567PdvL29YMa3+ksqbS7sDsVhnUJbLc26CQFn/aaAiypnM1+S1VjALX+noATQv72HXm/fIPy4/2kr+6G/y2vo6oqd3/1N3JcWZTJxTzZ71+M6DYY3FBSWQIuF7JRj+xtJC8vHVUns2DtG+wrP4SqKnTxiiPUL4KY8G5cM+oWIsM8iap+YaFs/m4h2xZ/V6sNLmspg0f0IzArHRQXKG7ADYpC30nXwoSrcB5PI3ulF0NViUeTwlmyN5cDK1J5akUqAE5FpcTpwlsj88Llfc/4nC3+IXQdMp3jP+5p3uupdJwifo2pqKigqKiI+++/H2/vjlP5WLhwdIAyHyL4OJsuuqEnX1fuZueydIZP79Qm465eei3v3TCIvv/8pQ1a2DI2p5sZr63j3knxRPi1vEentRRVRda0T++PqnJ2V2fS6Dwn80aETroM5+DhTP92KvFf/NVzglVk3rvkbfYeO8xT2x/mql9vAn0lrz/7HIEpR4jsG42ueyxfPPcIRfoq+o6ZzP/d8AxehoZXpR111TRGXTWtzu1Zqxey4atPKDmyEp1W48m7kaSaf548nPyqMIq8wgkw+GA8ns7Ch25AW08p8uv+tRJTE0qUH9+9Gkv3cY1ud7qKsmJUd+OvZ3uxWq2sX7+egIAANmzYQFRUlAg8hLOqvWNxEXycRXqjlgmXdePr57bx5Wu7uPzPfdHqW3+yzCixYmmnK35FUZj+6lpm9AnjphGd2qUNJ7V3Sfqz+dBy04IPgHeXzmOUOYIXr3in1u15lVn09u3NXbf+CYAd//43rioX2oXrcF0fR9HIOTi2b2bv6mO4I/ZxTdJA9M1MjI4cczmXj7n8jNt89fab9O8az7DxE/ju9S9Y//1KRl46Ac3vAke7W2XtpgxPUrAsI8ueXCNZlpAl6eT3yrE1BF/zfLPaqbhd+AZ2vGJ+AKtWrWLVqlXEx8cTFBTEPffcg79/63KSBKGjE8HHWRYa54PWrKX4YCnp+4vp3K91H4B2p5s5b23gnxf3bqMWNu6DlYtYdbiQv0wawZNLi+gR5sPjF7V/lUZVpd2Cj1xHKQe3HMRrj2cVV7vbwbjR44gf0Ua/F42eBRVfE7JsJ0ZZi6qqyKg1hcBVZCRSHaWguNnnKOJ/N2wh7cAWDmxdxrhr/g+D1kB+eT5p1WknD2nU63HNno2300HWytXYho1C6ZvEgthEsMHoomI6h7Y8ObohiqqirSnoNWLGWBYv/J70Vz5k8ODBdB95aurt1f0j2b0/H0X17KMoKuqJ72u+qorKddY8wqObO4zpWfelI8rLyyMiIoJrrrmmvZsiCOeMCD7OMlVVUQ0yVEFuVgWxvQLR6Jr+IVhRYefokSL6D/BMT3xnbQrhviYu6hPRpP2v+t+7FFXJ+Jl+twKqKtXkLZwiUXskIdZfh5deQ7nNzkMzx/LCkuV4Sw7emHtvk9t/Nqmq2mjZ67OlxFRJ32EJjJg0BYC9K7aTn51LPG0TfKyrPMLmYB1/8u+KS3WD5KkkcuK3qKAy/+BKxgf24+npH7H04etQM3NxZGfx01eL8O4zhLVRRiZ1OzVbRjqaAumZ6OIHUl5hI8UUyMHQWDoXZPNkn650Cjk7PQOqqiLXnPiDO4Ux9+4b2b96FyvX/FYr+Jg9q/Gp5PafP0PVN78wlyTVTGXtgBRFITv7zMnFgtCmOsBbQQQfZ5kkScx7fCiL3klmx4+pJG/I4abHhqA31n7pVUVFkiVsVifrV6ex4XABR8qtqICvXov061G6h3mzudKKr6np0+7+MqEfn2zYyZvzbml2299d8T1mg5Yrh09FljW8c0tXPvn1CT5e/hBXjHsSg67tizA1R2VJMW5H/UWwzoXTz2WqqlJZXklpdjF+EY0vNNiYHWW7CZWjGTfknga3eeLoF6wp2cfdm5/moW+3kXDwACVleRQ/8jqOo3lcr72IHn+eeHL7QnMYhgAtPlMmMezm6wgyWfj1UAajj7rx3bOPI72y6HL5KDQtqElzJqqq1sp30hsN9JsyhF27dzX/YPt/QDP5vubv194D3A3Ytm0bhw4d4oEHHmjvpgjCOSWCj3NAb9Ry5V/6k5dazlfPb2PhG7u55t4BHDtWzPzvDpBZbYeaEutaSWJQnB8zJ3elZ5cA9DrPuPihQ4WkZ5XzwvJsLo+2Mf+XhUT4WRjdcwi+5vpPdkeyj/DarzsYHd+y0ug3T7i41s+SJHHtxCf4aesHLFx+BROHvkhY4LmvOXKyPRpNg2uPnJPHP63TJaxLFKlHj/PZ+x/z50cbDhiaak7ilXyw6i1W71hC77iBBAaEoaoqbqeT3Qc2sOn4OkYpiUztcREpajZ7ehzBPWk2Rq0Br8FDiX7+UfKf3ELhkRyCunl+/0VBMfToPw41LgaNDAmqi4SESKTeUbgdDjIXbefAv5fS+5FZrW7/6RQV0o4dJb5XImafU4XpUqtzeOvpV5k2Yzqx/bqe8Riqy4Fj2YeoWm90vVpakrwDXO79zuLFi7nooouwWBpO9hWEC5EIPs6h0DgfJt7Uk5Xv7ueNpzZw2Oimwubi00fHNTp80L17EHGhKst2V1EQ6SLbHMyB3DI+2LAIRZVxuiX2FwTy+FQDXnqJn5LTsTpV/nHJeHpGnfmDvTkkSWL64HnsTh3GLxvvYWTSS3QK7dZmx28Ok48vWl17Fl86FfgEdwpj5u2X8+G/57fJkf013ixyLuPoviO4dryOW/FMu5UkCV+DL8MihjO785V8veszMuw5lM7QMr2kC/fe9S8w6jn4jxU4giW6h56qNZKafwB9eRXW1Cwk9URZTZBUyTMCp0rItrYP5voPGcLyn5ayfd0aRk+/6OTtjz/+ONUlFXz59qckpGcSFBBIcFQofrHBtXJ5HN+9grR/IWrUNPTz/tuiNnSU6qaZmZmEhITgdrv56KOPAOjd+9zlbwkCNK868tkigo9zLGFQGId/yyQ3o4JLru5KdKQ3qstJVVkB5uAoFIcTt2JDZ/RMs3O7nKR9+RUUSVCtJ2hGFD0S619bJS0/lR+3raWorIJn5swiIvDsFf/qG5eALD3Dup0v0WnqG2ftcc6sHU8oDeUPtFGTSo9n8Onux+nz3zPPJBnZZzIAux7+CkOPcFI2HkF1uUGFfvdPrLVteHwMOdVVuIJMGIxGpsy5sm0a24heA5PYtWkjXr+bOirLMpZAXy6bewX7N+4mMy2TH39dypVXXElUz7iT27nTDiGZOmO8/pFWtaO9cz5UVeXdd99Fq9USFRVFREQEN998c51ZP4JwLrR33RsRfLQDrd6Bxa0SvfdXpG160lQJ1aEiR6uomVr0BZHoZrmQ9Boq12Zi6ONL5NyLUNzKGWuFxIbEcdf0uHP2PHpF92ZncjsmykkSqErj27WRovw83nz5JbxMRqocTuK6J9TZpsJWxVvPvoZR48mHkZCwue1cPGc2Yd0aDwZ3vboCqcINikq+3s43H7yHW3GzPyObLiGBeFvq1n4YPGYsuyu20l9zMUpBJUigHV53DZQJF1/Cvh3bURWFjZs3n7PgA8CtKBhN9ZeS94sJYnjMBM92C5ys/nEFo3ZpCfGRPOv+RfeG9PWtevyqynJ0BiOqqvLrr6+Tk5PHzJm34e8f3arjNofb7SY+Pp5p06bh4+Mjgg7hD00EH+2gsrocSzeJ2MuvQGsxIWllXNYqivfuIuiywVQXpVH02y5UyUXULTPQWzxd5x1tcShZltEaOvPVmvlcPurWcx5Jewpqnbur2cK8PPz8/Ljrwb83uM1fHq+bDPnbx0upKCxrUvAhVbjp+4inN2Pfzu14FRaiqirV1dVExcSi+V1J/cMHDrJ3+1YqpDL6zB15xmMHhYYxZtoMAHbs2N5oW8qKU9my4XpUlw4VBVVRkFQT42d+i05ffyDREKfLhcmr8YJ0k26YRfGx3QR8PBqb1h8l8UFkjYQ89s5mPV6dx3fY8A6OxOWys359EaBFpzO26pjNJUkSkiSJGh6CgAg+zjmX001prkqnfr7o/MyApztWazITkjQCAEtoVyxXtV2extl05fj/8Pnym9h2pA9J8cPO8aNLqOew58NqteFUmv94iqJgraym4HgOqltFUjyznL2CffAKqJtoqNYUT+vV/9QaJyMnT6332OUlpZ58oSYEfps2vURR8U9IaIlNqGLZt781socTi3EISZOfRtZq0Gi0/LLoIo7s+pzwuAl4WULQaLVotFrPqsINUFUVu9OJycvcaBsBAjr1Jm/kM5jXP4tm11NUXPw+Qf3qH2psqn3F1axevBEWbwQgMNBGSsoWysvzCQ3rSreuoxo9xpYtWygsLMTtdqMoCvv27WPgwIE4HA4yMjKIjIykqKiIyMhI3G43brcbm82Gt7c3breboKAglBb8/QhCm2v/lA8RfJxrqgKq6iJlZwUfHv4JW6UGSYZhs7vQe1TblGA/lzQaLW45kuz8jajdhp7b3g9JQj2HH+ZeJiO+xuZfLedVF6Fus8GBClRZQpEUHFV2pGo3AaPi6DrhVK0LGQlbhRWTT+M9C4sWLWL3oSN4VZSgr65udPuqqlR6JjxMp05jm/0cTggJm0xK6sukZ7+DjBeqiicAVMGTvVp7e1Vyk18aDAwmKLxptWmQNYROvBPbwEvRv5JA9r5fCepXt7R7c0zuuY8NebGkpnmKqFVVufn2260AWCwHeeCBUVitpeza/To6rTdGkx+d4i7CbPasXaSqKnv37uXSSy9FlmVkWSYiIoII/1CMBSqFR3wJ7NWNCo0n2NBoNGg0Gmw2GxqNBrvdTmZmJnPmzGnV8xCEC4UIPs4xnUHDVY9OYPPi7egMGnwC/cg5VsjaL9LYsvgIiWMjGTilJ1rd+TMefOX4J/n4l2f5esVtzB77Olrtuan/oXoqR52TxwKQZKlFWeIOk0rw8G706Xtq0TSX00XKir1Y1+aw+2jRyWRIo02iNK0AU2Jso8etqqqiS5cuXHfddU26olZVqdXlLvqPvJf+NL3IXE7OPpL3vsDkmx5q9mMZ/cNJ902iy5F3Of65TKerm1dS/YSC3c9Trhxh+uQH+W3dOg4ccOJw6EjouYagIE8F2DVrFZzOb0/uU1FsxL7PiGVfMG6nCx/FhCvaiY/RQvWufOzHy4mzmlCtxRiSQokaGU/F95kEDQ3He8SpfBuf06YWR0Q0MfgShD8AEXy0A78QL6bMq93Nm59Wzs4Ve9i2JI/8tDJGXNofvxDTedETYtQZuGX6Eyza8Bmf/zwHo2U4kuzHgK6j6Bx+9sqwS8Cu5UuwHtx61h7jdCVlZS3aT5IkCgsLa92m1WmJn9qPykHlVOaVntpWlgjq1rSTVFZWFk6nk7S0NGJjGw9WVM59rS1V1SBJZ16d90x0w24jdYNExMX/aNZ+ZYc+5tixF3BhRydb6DHiJ1545WMAjMYqkgZ/W2t7m20p/fstZsvW29EQQei2i/C1hqCM9Kf7jH5sf+FnRtt6ULLwMLpwM94jI9FH107+1cd6U/TJAazJhQTd2AvZKD5eBaEh4t3RQYTE+jBl3kj8QnazbXER6cmbMQc4GHtNP+J6h7V385pk9vBrqLDOZNuRtTidZazb/gjF3R9kULfWjdc3JCi2E8O6JxLtZzgrx/+9ktJSDh473uz9wsLCqKioqPc+S5APliCfeu9rzAMPPMCnn35Kbm5uk4IPT/TRoodqsfLyKkpLChvfsAG245uJKN+FszwPg9eZC3HZCndTmrqQgsIVqKqb3iMWofftfPL+O+64guS9K/D3SyQh4XGS915NZeUhQCE8/M8EBydgsYxASlUJro6hOMBOePdQAAY+MKXRtupCzYT+dQAVqzIpXZxCwJz4Fj9vQbjQieCjgxlyUV96DrdRklvFxu93sOT1/UT1Osj020aha4MVcc82b5M34/pMB6CofDJL1t5KdnEGs4a0/bROSdbgFxKGf2DzZl60lGowUbBlG0ePHm1Sbovb7SY4OBin03lWakxoNBpkNBTmlJFyIPPk7fW1TZXLcLnKkM5xppmvbyD+AS0LrgA6Xf08WWv7E/nWAI70+TtRY2/AFFC3Zyhj2WxKlAzMxk506v4Qlk51q7SGhvYkNLTnyZ+HDF4MQGbmZxw99hxFRX2prt6BPuoIh4IMhO+Mo2RJJcH3XNLk9koaGVeJDa/+bb9AnyC0qXauuyeCjw7IO8CId4CR6ISJHN6awcqPDvLh33/BJwRC4wLoMaQ7oXE+7V4kpjGBPoFcNfkTvl39KAt+3s4NU/7T5o9xLl8Cb29vEhISKCoqOuN2J2arbNq0CUVRUFWVsWPHnpU2qdVGMlLLKT12sJ47T31rK0ondoIBf/9zezVuMnnjcGSwdKknIG3wF3Z6r8zv4iO3y0F63DhiDBqK352DyzcGTXQSUdPuO3m8cncWXQf8F6/w0c1uY1TUNXh792L3npsJDIwE9c8oXhJRd02m6KXNlB7ei3enHuz/djl6kxfxM8fUH+A53VTvLkDSSBi7+DW7HYLwRyKp7V3273fKy8vx9fWlrKysVrLWH1lRdiV71x2gNK+MvBQ3TquOmEQtM+4YhdyOa5s0xyfL5mH0nsqcEVe02TGf+GEffxrZieiAc9Pz0VxPPPEEf/vb3zCbmzbFtCW+XrCUmLgoBo/pc8bt3r7vexLGuJE1suefLJ/8XqPRIGs0Nbef+l6j1WLx9SM0un2nfaen7+HI0ZeZMP59VEWhMHkFZTu+wViWQsSdP2LNW8/+3X8mafqBVkWjqqqyc9d1eHv3pltXTy2X8vSDFH6VzNHKDNBKaLU6ctOPIcsyLqeDK//7PIUHU9j/80oiSmKJmJiI99goZIO4rhM6rnfvW8OAqbEMmNyE4dpmaM75W7xDzgOBERbGXJEEgOJWOLQlk5UfHWbV51sZP7eli2ydW1dPeoMvll1KUcV4Ar3rVt9siQ4WN9fRJcif7994xXNFr6qeiTmqUjNBRz3Z/pPThdWaNRdUz31Ou4IUlICk0Z42qafmG9Uz76akvJCYTo0XL3PbvfELllHcCorbjVtxo7gUnC4XdrfDc7uioLpVFEVBqfmac9jF9U+0b/Ch1epRFBcAkiwT3HcSwX0nkfb6xRTsWobJ346kuFvdDSZJEmFhl5CW9vbJ4MMnpgfvbf8/NFoNf37/S7Q6Hc4qG85qG988/Cgak56tny1E8YL0OBcHdmzDvq6awow0kmZdxsCLLkGnPzc5SYLQVB3ho1MEH+cZWSOTMCwGW1U1G77OpqpsNeOvGYLZ79xWa2wujcZIfLeHWLrmRnp0e5Ck+NHYnG52ppciSTCkU0CzhpF2pJewYGMad47vuMXYLLZKYgcPQ2cwIEmy5/nVVLk8sZCgJMsnK18iSUhINSv1Sqx6/xP69ulFSFwYJ8YkJMnzH1mSam6SCI9qPJgzeOlJHH7mCqj1+fy5j5u9T1vT6Qw4ndns2vUxWp0Xep0Zvd6Ce9QtVC57Bmu0L2VhbVPvpdw0gpeq03li9UJMGh0uFcb8/SYilv3A+kXPM+aKh9GZjWhMesqrClh4z4PILpnZzz19cpHD8sICFJeL9L272fDVp4y5dl6btE0Q2lJ7L7Yogo/zVL8J3dEZdKz+NI2ljgX0npqOVmvBbs/DzzeJ4OBJGAwdK+ktKX4UkUGd+XXri6SnPMqqvFvpETOUaoeLd9akIElgdynoNDISYNDJyJJEhJ+J/HIbnYIs9Irwodzm5PMt6Sz+y0hCvDtu0KXTakkcMhxdCwqTAWzQexMWGUJUl7aoD6FitzqRNTKeOEc6GcicnmTR2OrK7cHfP4rg4Euors7E7bae+qfYkAflIUl5RPs2PhvlTCodZTy3bzXflvnxQEQP5vWYjqK4UFSV/x1awf4sOy419eT2siwz79X5GHwsSDrNycDZ7XLhExSMy+mkrCAPnaHu795VZKVqay7aABNeA0KQtB3vNReEs00EH+cpSZLoPaoLWYesVBT5EBszGbfbhtEYQUnJJg4cfBh/v8FERV2LRtNxciIiAiKZPfxmDhzK4tGkJEID6++5UBQVh1tBUVXSiqoJ9zVyJL+Sw3kVWAxa5l83iADzuSlm1lIqQCtzctoqoXaQTiLlhe01Qztw4hsfq2c4wyaBPDiczrM7Xk+SVqsjadBd9d736Ob5rKnywVzuoNOW75geFsFFMc0bilybs4tHDmdxS6Q/+/qNPBlIyLIWGbin51S+mF3O/hU7eOrfz3LDvJuJCQ7GGOCLqqik/7INxelGt9ZJqbYQg9uE+cY4tny3kNv++T4l3x1FNmhQnQrOQitaXwOmPkE4MirIenQ9YX8bhDaw8XVvBOFCIoKP89T+9dlkHy7l6LZ8zw2uPnj7eE7GISFTCA6eRH7+T+zecxsmYxReXnFER/8JcGO35+N2VyPLRozGMGT53I1J5+QsIi//R/r1eQO9PrDB7WRZwih7phYnhHsSl5LiAkiKCzgn7WwTqtrqrs22mtGkMWhIeGxordsqMioo+98uLHf0wbGrEMXuapPHOlccbjeZShBdTG7eG3Idu4oO8ezhvbyfkUOMwc3E4HAuij3zekPLM3fyr5RcXkzoRlJIwzOBrhp3BeXDZ3PbC1fx5f+KudQxBZtaidatwxHoQuOjx29eL6LiR5H80LfYlx5hSpc/4UypwDIs3LOmj05G629E0sq4KxxU/JZB4E29ROAhnHsdIOlDBB/nGbdLYfP3Kez8JR2AoGgLZj8DWn3trltJkgkNnYGvb39stmys1gySk+9AkvUYDMFoNRbcbivV1rSafARNzRodCioKEjI6fQAJPZ5r8ATodJbicBTh5dW5SSfJ8vI9FBWvoW+fd5Ckjl+zpLUOb1pH5wFJ6Aw1wZ0k0XnA4JO5ARXFheQc/t0U2dNeR1tlEdJZ7JH3jvbG+zlPpd3s71MwhNXtIVMUFVvViQJpUp2vslZCb2ifk+ft25YRoLHzjz7TkWWZAcEJLAxO4JfMbaRVV3Jfiouvsr9muK+JKC9fpscMrzOs9ErKEb4aOJY0pxelThePHskizWqnt7eJUL2OP0eH8OyKw3yw8hj+ERIjnV5UYSa5YjO9eibS7Y4ZddoVfsMAnCVVhCb1QNbW/3de8NZu9HG+mLqfR8G0cGERdT6EpirKquTXD/dTnFVF0ow4BkyJRdtI4TGjMQKjMQI/v0GEh89ucDtFcSJJGqTTznapqW+Qlv42EhKFhSvRaM3IsgGd1hebPQe9zvPB6eXVibi4O2vtC1BWvhu7PRdrdRqVVYdQFAfduj3yhwg8AK55+kWKszJx2u2AJxgJCI8kKCYOgKNbN1FekE9wTFy9M3cCYwZh8vZt8eMf//EYVQeLkSQJjb2REucF1YRf06POzb4hCj++tajeNW2qinxRFDsTb0ogtvuZp/q2NavLytLqSLYOGoCv0a/WfZOiBgFwczzsLNjPvvIifiwo46W0HzBoNARrVWaEhtDHNxSXZGJblZ6b9x09uf+MYF9AYllhGa+n5yNpPc+9rPwIozYn42dNw+CSMHkNo/BfH+N26LH0ldH3TkDXvTdBPeIabb//Zd0oXdr8armCcKEQwcd5wF7tZNtPaST/lolviIk5fx9EcIx34zs2gyzr6twWG3sbGRkL0Got9O//EbKsx+ksw+2uwmj0JEGqqsqxlBfYsvViwsMvRZZ02Ow5VFYewGEvJDRsFj4+fQgOnoyXV1ybtrmjC+/anfCu3U/+XJydWecUHtO7L536Dax3/6LsQ2h0LX+LViYXETw5BmOAEa2p7u/3dKpWxlhPmfqLbr7xjPv9+vmXOGzWFrexpZKLjtFZysCsOfM04/7BPekfDNd2AafbTqG1hKyqfF5NOcZjaRJlajTPp+ZwX2woPS0mupgMJHjX7slRVZVj/bviow4iNXAlA6/9GNlsQarpRan6aQ3O1FxKPigh8vEKJK+6783yVRko5Q40vnpUl4r9eJkovy78oYngo4NT3AqrPz/Mka15DJgaS9KMuHO24q0kaYiJqT1NUKfzRafzPW0bia5d/kZU5Fyqqo6h4sbPLwlT3N1oNKK+wekkScJhteJ02NFotY3mgyhqKxNOVRW/Tr4Ym5hTcOjDfaft6+mV9esXTFhSw2sLlRVU4na1fOG4lnrt+HFS1GieObCWFwY23KN3Op3GQLgljHBLGB+FNr2nRpIkuvqbUZ0asnCh8a5dPMk8bTSVn3+Jj+YwkteoOvtb9xfhLrPjPTISR2YlrmIbAVd1R2Pp2AnTwoWr/TM+RPDR4ThsLo7tKMBpd1FV6uDItjwqimz0GRfFsEu6tHfzGnRieEdoWET3BHb/shS3y4XicqK43Yy6+oYGt1dVtabmR8uoilonF6jBtl3dnerc6lq32TIqKN6Yc8bgo6JQpkvigBa3saWsLs9Q1oTQzo1s2Xb27viO0vD6e6nK93oTekvdFZxVVaV44WEiHh7iSTgVyaVCB9Heq3OI4KMDyU8r5+d39lJeaPPM9rDoiOkZQN87YgiKOvOKnkLH17l/Ep37JzV5e1uFs0WzXY7tLMBW6SCgyonb5kbbhBE6//gA/ONrJz8W7C4gf01mA3t4GLw06PTnttbKMwd3st0ZzdK+IcT7hFLtVtBIoEFCI7XdDKHfq3YrBOZuIy1tN7GxfWvdJ2ttSL7BtW5zVzkp/zkVn3HRSDpRy0MQTieCj3akKCpFmZU47W4yDhSzY3kaQZEWZt7dD58g08liUMIfU2WJDYO5eW/R3SsyWLfwCAADggxoUsoID25hnReXgtro39+5//ucFBTA/qINvHggFTcSCjIKEooqoTSjPTZVwy5XDFsGhRDj3Xiv3ZDh17BF1mBYdDv8dePJ25XSMlSXDtBh3VtIxdosFKsTrb8Ry+goscicINRDBB/tQFVVirIqWffVEbIOlwKg1cn0HRfN4FmdzllOh9Cxefka0Giad8WcODaSimIru1dkEhjjQ9GKdEq35HrurCnHfno8cep76cT/T8YTaoUDewesvpkUFMsnQa1fEOuvW79lVyWE/G62TEP2b12IfudHBN743akbHVVUv/53VOliihZlI5u0BN3UC0kri8qlQsfVAZI+RPBxjpTmVbP5hxQKMipwWF1YK5wYLTqm3ZaIX6gXPsFGEXQItaTuKWTVZ4dQFRWH1YWqqEgaCVn2rP+i1WsYfVV8rZWNZY3M/vU5ePnoibmiG+VpFXgWscNT1PTElN4TlU7VmnpDJxa+O7EtkHe8nPSMcurPcqg5TAcoVtRSLw26hMrNX3P3zgzeHjzzjNtu+O5RbA4rg2/8AoukQlURuO3w6gC8htyHzi8I/aBeoqdSEJpIBB/nQMrOApa/vw+TRUeXgSHo9Boi4v0I6+SLziACDqF+f3pxFC6HgiSD3qhFliUUVa1ZeVZl5UcHUFwK8u9qvUy5uReLX98DOg0hfYMbOHrjrFoZJbOywftVVTmvT7aqqrDD6sNzXc689DdAzwOf43fJy7D6GTiwGGKGgNMKt61BDo5HzOsShOYRwcdZpqoqa786TEQ3P6bfnthoUTBBOMFo1oG59m2n//VodHK9vaeBURY0OtmzfyudKbRQ3M5GtujYZFnLWEsF3+VaGRFuxayrfyZKpctNuTEAv+pi6H8dTHmm/acKCMJ5rlmDkm+++SZ9+vTBx8cHHx8fhg0bxk8//VTvtrfddhuSJPHyyy+3RTvPWxVFNipL7CSOjRKBh9CmJKh37FbWyCjuNhgOUdUzxhYulxNZe/4OuwC8OGgOKQ4D7x9e3uA2P+SXsuXqn2HgDRDaUwQewnmvI7xrm9XzERUVxXPPPUfXrp6VLxcsWMDFF1/Mzp076dXr1Bz37777js2bNxMRIeo+aGqm2Dms59eiXcJ5QJLqzblI21OIb3Drp7+efmRnVRVv37+ZMHMWQcEuTBYdWpMWnbWIsn1vo/GORefXFZ05Cvk8KS5XZCtne3E2B5yBfNKpU73bOBSFL3OL+aJvx62xIwgt0d5Dps0KPmbOrJ2U9fTTT/Pmm2+yadOmk8FHVlYWd911Fz///DMzZtRddOmPSNZKWCsc7d0M4QIjSdR7CdMtKYRVnx/iwPpsEka04gLgtGNbczPRSjbG35KE1qjDWliEtaiYgMDDqMe34qoqwF1dgt1R5VmgEFBViZxXgCmdkP390AYGogsIRh8cgT4kGkNwLMbgODTnuE7ICdM2rWe0uYJveiUS5BVS7zYaSUInSbjO48RaQeiIWpzz4Xa7WbhwIVVVVQwb5lm2WlEUrrvuOv72t7/V6gk5E7vdjr1m4S2A8vLyljapQ8lPK2fhs9sAz9h95/4tT/wThHpJ9XefavVaLrqzL6s/P8SeVZlMmteLgHBzPVs2zaGvvmXLOjexfkX495gOgHfciZ6AqQ3vqCiU/ziEwPv/gy0/DXtBJs7CXKr276Bs3a8oxaUoZZWgqFSnOHhl5nW4fMz4mGT8TVr8LQYCzWYCLBaCvf0I8vEnwGzA12REp5UBuWZF5lPfe742fEWnqiqKqlBiK8FHsnFvz4lsL05jS8FhBgV2rbPqrUaSuC06mPcyC/hrXMOVXgXhvNIBgulmBx/JyckMGzYMm82GxWJh0aJF9OzZE4B///vfaLVa7r777iYf79lnn+XJJ59sbjM6vGM78k9+f80TQzB5i3UchLYlIVFRZOXHTw/V+ftyWF3EJASQvDqLz5/cTP/JMQy/tGuzjq+qYK+wsmujlVn3DMW3SzOHHmRPrQtzTG/MMb3PuOl3M+fy6s3XYvE3UVBWQEFFEYXlJRRWlJNXksWBzGOUVjsps2k4UJ1Fmd/XAPT1CUBzogtIrW/t3dqkmlomiqpS5Qrhut9+w6IPoKjiAOWOcj6fOp/e/jE1z19leVE5n2YXMTW45asLC4JQV7ODj+7du7Nr1y5KS0v55ptvuOGGG1i9ejVWq5VXXnmFHTt2NGss6aGHHuK+++47+XN5eTnR0dHNbVaHUVliZ+1Xh0nZWUBsYiCjrugmAg/hrAjt5MPmH47Td3w03ZJCT97usLl49761lOVXc90zw/EJaNmwhmK3UZzn4LKrgmsHHqpKecZSrLkbUBQ7ituGIagv/jGXojEFtuy5ZBzB5GVArzMRGRRDZFBMg9uqqkqfjzzBx819X2ds58QWPebpql0uxvxwG49ufZvvJv8LgORKK1/mFPNsfBSRRvEeFoS21OzgQ6/Xn0w4HTRoEFu3buWVV14hISGB/Px8YmJOfWi43W7uv/9+Xn75ZVJTU+s9nsFgwGA4PxLUzuTw1lz2r80mN6UcvUnDlFt602VAcLsn9QgXrsSxUSSOjaI0r5qPH9uIyaLDZNGhqjB2bnd6niHfozSvmvIiK4pLxe1WUFwqilshtJMPJVtWUJSSQ0aahgGJ/oSOuvjkfqqqcmTFRTjdFfgHDEej90YjB3L82H9RqvIIGfBoi55LTlQ3wjLy6JTQ+EJxkiTx2eQlXLN8Bn9Zew17Ou1p9fvs7s3vE2DwZtGkp6h0ufk8p5gVReX8KSpIBB6CcBa0us6HqqrY7Xauu+46Jk6cWOu+KVOmcN1113HTTTe19mE6tNTkQn55fz8RXf0YND2OxHFRGEyihIpw9h3fXcDSN5OZ/cAAIrr6Nbq94lY4sCGHvWuy6DE0HK1eRtZIyBqZsgIr5fkVbFlqYeqsrgy8axzS78q7Vxz7GhQnvaasqXW7y5pfk3PRMgETJ3Bw8YomBR8AieExbJu7g6u+foQrv36Ul6c8QISPf4sfX3aXkiL1ZO6eFIyyzOxQf+b3isVXJ97HwgWo/VM+mhd8PPzww0ybNo3o6GgqKir44osvWLVqFcuWLSMwMJDAwNpdrjqdjrCwMLp3796mje5o9qzMANVzJSp6O4RzSdbIdO4XzO4VGexYlobBrCU42pugaG+Coix1Co05bG6ObMtn2OwuRCcE1PpbzTxUQv7xUkIsuZiD4pFkCaqLayWnlWZ8T2DU7HpaotKagmNdp40j77LZKPf/qU7SZ0MMWh0fzX6S4V8M5k8/VDG7x0RuHXRRsx53V/4uXt/5OpHekWwadzOBpoDGdxKEC0E7n6aaFXzk5eVx3XXXkZOTg6+vL3369GHZsmVMmjTpbLXvvDB4ZmcyDmzn53f2kjQjjsEzm3b1JgitFds7kNjep4J+a6WDwoxK8lPL2b8uG3u1C51BJijKQlC0N/5hZoxmHTE96+ZmqJWFHFuzn4pqIyGurfDu/4GqeAprATiqqNTuIjTpmbr7ouByVeCqzKTYJWPUeiFJEuWyHntJCbLRiCRJyDodsuZUsT3F6WLlih2ULlqEPHAsiS4VfTNGObwNJp4e/A6PbLmFD/YUMbfPJMz6pg/j/mfrf3hhzAtEWERNIkE4l5oVfLz33nvNOnhDeR4XmrDOvhi8tNirXeQdvzCmCgvnJ5NFT3RCANEJp67gHTYXRVlVFGZUkLKzAC+fes7uqkrw92Pp6RpGZLwd+ZgO5i4Er9o9AaUbx6M3100ItwQNI+3YKxSvW80Ew/+41H4IgG3XPsKdL76IqiigqmQDf3/66ZO9G1kPfo1/pRWX7wh0sQHseWI9g54Z3aznPCthKEXV/+Wl3U8w5JMRJHiP485BVzO204Az7qeqKgaNgXBzeLMeTxCE1hMDmm1k4k09WfK/PRRlV+F2KicrmwpCe9MbtYR38SW8yxmmi0oSxn9m0Vh1Hqs1nZ07ryXI72bKclUUtxufwECCwkdRfSQHk8WHCfnree3S29DIWib+tJYb/vWvk/u/8uCDtQ8oqwx851RO2Iqn1pOZUYbJqCUwuOm1SW4aOImbBk5i2eEdzN/1EX9ZcwM7Ynah0zS8pIEkSUzrNI3Xdr7G3QOaXh5AEM53HSDlo3lruwj1qyqzs/7rowDYqpzYRSl14QI1YfxRDvwwjx//o7LmIyjIqGLxfzfw09uPsn7BSoqzs+nx2zZcLqXe/YPMZj58+BHm/9/97HtwAl5S7cRVqbMP/G8Ph7bltKh9U+MH8MFMz7DQgE/6Nbr9lLgprMpc1aLHEoTzWXunJoqejzZQVWqnNK+akFhvJv2pV/3d2oJwgbjykbEobpXCjAp+eHU3uJcxYNqlTJrXDf/gBFYdeOTkldXvr7Dm/uMfZK35GPeGN9BrjXjb99W6PzQ+EJJLGT6teQXRTiisKmfc1yMA+GzyL41ub9FZ8DP4teixBEFoOdHz0QZCYn2w+BvQ6jX4hXi1d3ME4azS6jTojVoiuvlzy0ujcVRnsuWr1TirPImeqsNORmFRvftmLP8fASsfQDfxYYLu+hHFJmH74FGU/HQAslelcyiy/qXtmyK1NBuA7y/6lcTwxsuhb8vbRpQlqsWPJwhCy4iejzbgdilUVzg8UxMF4Q9Eo5W5/8vF7P5lKRu//pz+U2eSNH4yH7/7Fn9/5B+gKLgcDspTd2D7+lZ0uFk3ZT6P5mtI23iUgQNvY8muO3AWXYocEkO1XsZSZmfFv9YDEFGlsKw8A5ttNXavujkgUlk+/W6/h+/zfqWguoRU108AWAyNBzAHiw/y9p63eXX8q237oghCR9cBkj5E8NEGNFqZ3qMiObgpF1ulE6NF1/hOgnAB6T58NP7hkRzetBaN1YouOo57D6bz+v23s9vHB6/ycuY8GoPd1Itu5U76KBW86CfxenUveKKME++Yi+8ZXOu4G+9fzeBhQZSWjmHGXdfUedxPP/+BjZ98SI+SVC5+6G5mJf67yXV2Ptn/CX/p/xfMupYvuicI56/2vVgWwUcbGTgtjgMbc9i69Dijrohv7+YIwjllNFuI6d2XmN59AZhec3tKt67s9SnB2nckXUIicDoK6Hv8P8zqej06AgixHQP6njyOvbSEsryduF1WVLeCKSILm64LituTwJp1KI2AyBBMFk/PxtyrZ2GfPYnXb7ic/D2bkPpMaXKby+xlJAa1fl0YQRCaTwQfbcTLR0+fcVHs/CWd4bO7iqm2ggAE3n47vyY/jauvwg+Tn2T10rvYrVHRoCDl7+fJI99gqxhB6p53KC/dg0YyYjH0QitbQCNR3PMz7GlXcXjDMhY5bKRsW4LOFIreZMFWkUtgQh8OZ2yg940zuHLaHU1ul91tx+qyopEbnoorCMLZI4KPNlSaV43iUpE0IvdDEAB8Z8xg/owZjPlyLNM/u5MyxyZm2qrgwA7cgNVZxJHV9xAdfCPdJjyI5neLuB1e9ANS2FJGXX8vBqMvPUYMpsfQRCRZ4sjW/RQVlpJWEUDGRh8OJR6je1SX+hvyO+8mv8vchLln4RkLQsendoCkDxF8tCGn3Q3AsR35dBsU2sjWgvDHcXvn93ho0Q66h04lWbGyX/JkeRSo/fnpor82uJ/OoEUyHqCk8iWkSh+oUsn4UQJkUGVUVcNfH3qJDTsO8dNPm3HONJBSXMDkbr0w6uqf8m51WdmRt4M7+ja9p0QQLjSizscFZPodffjsiU3sWZkpgg9BOM3VSV24Oqlur8QlG5dz8brvKFc0FLv1LE7qR7Tl1Htn4vTFdfZRVRVVdaMoLr77eTLXvrwBu0tPsc7F0kW/cCTDn+X3hdEtqP6y6XpZj1t141Jc6DWiJo8gtAcRfLQBxa2wdUkqBzfmUFliJ7J7y5f2FoQ/Eh9zVz7q05l/7f6B14tDSdqawyTjOrqZdHSxeBPvE4qqqpzoKFY5EXyo5JflUahJ4rt/1F7JNun5DxoMPAA0soZZXWbx0/GfuLjrxWf1+QmCUD8RfLSBI9vy2bY0Ff8wL2bd3Y/IHiL4EISmWF5Uzp/3p9E/YBi5fYMpd1RypNTAgbJc1heXsLus1DMhsKaLWEI6WRlxdYUvwyyX1TpeudWGVlt/afcT7G47W3O3MiWu6TNjBOGC0v4pHyL4aAvV5Q4ASnKr0Rk1yKLYmCA0Se64fpQ5XQzcuJ9CpwtvjcyforozMCSBaxvZd8aKvYyNqj28uSrlEDGBDdfZKagu4LH1j3FNwjWMjmre6rmCILQdEXy0AblmdkunvkGExvm0c2sE4fziq9OyYUgChU4XLxzPZfeBdEJ0MtN2/AevHemk27uCJKEC2Q4nv82YjarTkeqSmBDdo9axNqam0ScyuM5jONwOvjj4Beuy1vH3IX+ns2/nc/TsBEGojwg+2kBAuKdCom+IlyixLggtEGLQEWLQ8WpCDEVOF7LTSpArj9QfjzDo++eRzBYkJFIeuJ9+W1cTde+9vDr/Y0wzRtQ6zt7sUv4+aWid49+8/GZmdJrBW5PeQpZEDR5BaG8i+GgD9moX0P5TlwThfGfRarBoNeAqgWPL8Rs5FuvNc9B0CmWPsQS/3CqqbTs5sv1jErsOBu6qtX9emZvBUXV7Ne7sdycr01eKwEMQoEPkfIh3Yiu5HG5WfHSAmF4BDJ7Zqb2bIwgXBoNn+DL8gduo+N/DPBOZQ0oXP36+cwL/vNSI1h6Kv7F2D4eiKKio6LR1r6mGhA8htyqXCkfFOWm+IHR07X2xLHo+WsntVlFcCv5hZrQ6UapZENqE3gtmvAip60jf+wGbuwdjqepKWFkgPw3+mS2/pGLv5M1vh/LJLbORU2bjUF4hYX4NHzLON46jpUfpH9L/nD0NQRDqJ4KPVtIbNUTG+7F7RQYRXf3o3L9uspsgCC2QdDMAUwc8ytgDRcjmmlksDpU0i4b9Djt9iqsJ9zXROUQLPquZ4Od3cvcqZxW78ndxqOQQFp2Fn47/xJioMe3wRAShY+kAoy4i+GiNgvQKVn16kPy0CnyCTfiGmtq7SYJwwdGFeKEL8ap127xBYSe/X7BvAd8c3Yi/wR8qg7l75d24FBdeOi96B/YmMSiRamc18yfNp5OvGBoVBKDdx11E8NFCTrubtV8dpqLYxsy7+xKdEIDU3oNogvAHk1mRyQvbXmBQ6CBigmIYFjGMXv16odM0XOtDEIT2J4KPZnI53az65BBHtuehKjD++h7E9Axs72YJwh/SppxNTIqdxLOjnsWgMbR3cwRBaCIRfDSDoqj8+sF+UpOLGDqrC536BuEX6tX4joIgnBVz4ucwJ35OezdDEM4vavtnfYjgo4ncLoVfP9xPys4CJs7rSXxSWOM7CYIgCIJQhwg+mmjXr+kc3ZbPtNsSxYwWQRAEQWgFUWSsCRS3wvHdhUT3DBCBhyAIgiC0kuj5qKGqKmX5VmxVTvaty6YosxJZIxEc403OsTKKsiqZeVff9m6mIAiCILRK+2d8iODjpH1rslj9+WEAjGYdnfsF4XIqZB4swSfQyLhrB4kVawVBEIQLQntXhhDBR43I7v4nv7/qscGY/cS0PUEQBEE4G0TORw3/MDNznxyKzqhh94qM9m6OIAiCIFywRPBxGr9QL7oPCePItrz2boogCIIgnB0dIOlDBB+nURSVsgKrGHIRBEEQhLNIBB81SvOq+fb57WQcKKb/pJj2bo4gCIIgXLBEwimeabbfvrgDa7mDS/82kPAuvu3dJEEQBEG4YImeD0CSJGJ7BgCw+vND/PbxAY5uz0dVOsDAmCAIgiBcYETPR40xc7sT3tWP3ONl5B4vZ//6HBLHRTH6yvj2bpogCIIgtCmpnQt9iJ6PGlqdhp4jIxh/XQIDpsQCcHx3QTu3ShAEQRAuPCL4qEdRZiUAAybHtnNLBEEQBOHCI4KPegy9pDMBEWYObsxp76YIgiAIQptR1Y6RyyiCj3rIGhmXw01IrFjLRRAEQbgAtfPaLiL4aIDZz0BVmb29myEIgiAIFxwRfNRDUVTyUsoJjvFu76YIgiAIwgVHBB/1SN1TiKKoRHTza++mCIIgCELb6RgpHyL4+L2CjAp++WA/MT0DRPAhCIIgCGeBCD5+Z9N3KXj7G5h6W2K7F2ERBEEQhAuRCD5OU1liJ31fEfGDQ9HqxUsjCIIgCGeDOMOeRlVVtDqZzT8cZ/03R9u7OYIgCILQpjpIykfzgo8333yTPn364OPjg4+PD8OGDeOnn346ef8TTzxBjx49MJvN+Pv7M3HiRDZv3tzmjT5bvAOMXPvUMCK6+ZG8KpOMA8Xt3SRBEARBaHPtnVXQrOAjKiqK5557jm3btrFt2zbGjx/PxRdfzL59+wCIj4/n9ddfJzk5mXXr1hEXF8fkyZMpKDh/1kgx+xmYeXdffINMbPkxhR0/p/HFU5tJ2Vn7Obgcbhw2F26X0mEqxgmCIAjC+UBSW3nmDAgI4Pnnn+dPf/pTnfvKy8vx9fXl119/ZcKECU063ol9ysrK8PFpvwqj+9dn89vHBwHwCTZRUWilU99gzH4G7NVOjmzLR1VOvXRmXz1hnX0ZdmlXfINN7dVsQRAEQWiQ4lZ4885VjL++BwnDI9r02M05f2tb+iBut5uFCxdSVVXFsGHD6tzvcDh4++238fX1pW/fvi19mHbTc0QEfqFeOO1uohMC2Lk8jYwDxZQVVCPJEkkz4vAL8UJxK7icCpUldg5tymXRC9u56vEhGM269n4KgiAIgtCA9h13aXbwkZyczLBhw7DZbFgsFhYtWkTPnj1P3r948WKuuuoqqqurCQ8P55dffiEoKKjB49ntduz2U2XMy8vLm9uksyaiq9/J7wdOjWPg1Lgzbt9rVCSfPLaRQ5ty6Tsh+uw2ThAEQRDOU82e7dK9e3d27drFpk2buOOOO7jhhhvYv3//yfvHjRvHrl272LBhA1OnTuWKK64gPz+/weM9++yz+Pr6nvwXHX3+nrQt/gbCuviwd00W25YeJzelrL2bJAiCIAgdTqtzPiZOnEiXLl2YP39+vfd369aNefPm8dBDD9V7f309H9HR0e2e89FSBzbksPKjA4AnefXG50a0c4sEQRAEwcPtVnjrzlWMvz6BhOHhbXrsc5LzcYKqqrWCh+bebzAYMBgMrW1Gh5EwPJyIbr4seSO5VkKqIAiCIHQU7T3VtlnBx8MPP8y0adOIjo6moqKCL774glWrVrFs2TKqqqp4+umnmTVrFuHh4RQVFfHGG2+QmZnJ5Zdffrba3yFlHS6lJKeKi+46/xJtBUEQBOFsa1bwkZeXx3XXXUdOTg6+vr706dOHZcuWMWnSJGw2GwcPHmTBggUUFhYSGBhIUlISa9eupVevXmer/R1STM8AvAOM/PLBPq5+bAhmvwunZ0cQBEEQWqtZwcd7773X4H1Go5Fvv/221Q26EFj8jUy7I5Gvnt5KUXalCD4EQRCEjqGDZAOItV3OEke1C/CUbBcEQRCEDuV8Kq8uNF15kQ0A70ARfAiCIAjC6UTwcRY4HW5Skwvx8tWj1WnauzmCIAiC0KG0eqqtcIrT7ubwllx2Lk+nssTO6Kvj27tJgiAIgnBKB8n5EMFHGynIqGDJ//ZQXWYntncgM+7sg3+Yub2bJQiCIAh1tHPKhwg+2kJ+WjnfvrCDgHAzs+8fIFa1FQRBEIQzEMFHG8g4UIzqVpn9wAB0epHjIQiCIAhnIhJOW6Gq1E7u8TL2/JaJoqiU5FS1d5MEQRAEoUFqB0n6ED0fp3Ha3Wz6/hh5x8vp3C8Yv1AvvHz0GLy06E1abJVOSvOqKUivIPNQCXnHy0/uqzVoMJp17dh6QRAEQWiidl7cRQQfNRRFZdn8ZLKPlBIR78fWxcdxOZUz7tNlQDDdh4QRGGXBJ1DkeQiCIAhCU4jgo8am746RcaCYGXf1JbZXIKqqYq1wYq1wYK924rC5UVwqIXHemLz1aLRixEoQBEEQWkIEH0DqnkJ2Lk9n2OwuxPYKBECSJLx89Hj56Nu5dYIgCILQRjpGyodIOHXYXPy6YD9xfYLoPymmvZsjCIIgCBe8P3TPR1WZnVWfHsJhdTPqim5IcnuXXREEQRCEC98fNvgoya3ix9d2U1FkY/LNvfAJEgmjgiAIgnAu/KGCD1VV2b4sjZyjpaTvK8Zo1jHt9kQ69wtu76YJgiAIwlnXQVI+/ljBR3W5g83fp2Dw0tJtUAjDL+uGxd/Q3s0SBEEQhHOqnct8/LGCD5O3HpO3Dq1Ow+Sbe7d3cwRBEAThD+kPNdvFXuXEWuGkothGRbGtvZsjCIIgCOdWBxl3+UMFH4e35J38ftev6e3YEkEQBEFoR+087PKHCj56DA8/+X1YZ992bIkgCIIg/HH9oYKPE6vOBsd4021QaDu3RhAEQRD+mP5QwcehzbmAZxE5QRAEQfijUdWOcf77Q812MVo8S94XZVay9M09hHXxJaKrH8HR3mh0f6g4TBAEQfgDk9o56eMPFXwkTY8jvLMvOcfKyDlWytbFx3E5FDQ6mZBYb8K7+hHexZewzv/f3r0HR1WffQD/nr3fsmez2SS7myvJRiHcRXkBi6ioDEWlM9VSaUWkg6/tMFpHp9MyVpQZUYpD7U2nVV91WisWsOMNKSqEagHfcPEFRCUbcgGy4b6bcEmy2f29f5zNCeEmCZs9u8n3M5Nxspzs/vKYy5PfeZ7nJ8NiN2q9XCIiogFpUCUfOr0OxcNzUJw4uTYWi+Po/pNoro0gFAzjq00hbF/bAABw++3wlctqQpKVY4Gk9VQWIiKiAWBQJR/n0ut1yC91Ir/UidFTiyCEQMvRMwgFIwjVRtBUQRHW9gAAGAJJREFUE8aXnzYBAOyyCb6AS71Vk1Ngh07PWzVERES9NaiTj3NJkgQ51wY514ahE5W23LaTUYT2KTsjzbURbHo7iHingNGsR/4Qp7ozkj/ECZOF4SQiogzA8erpzeIwYsgoD4aM8gAAOqMxHG5oVW/V7NywH9Xv10HSSfAUOnrcqrG7eG4MERHRuZh89JLBqIc/4II/4AKmlUDEBU40n0aoNoxQbQT1u45i54YDAACnxwJvuQxfuQu+gAy31w5Jx7oRIiIa3Jh8XCFJJ8Htt8Ptt2P45AIAwKlIO0LBiLI7UhtGTfVhiLiA2WZIJCNKQpJXmgWDUa/xZ0BERINGeoz5YPLRH+yyGYFxeQiMywMAdLR14nB9S6LFN4JtHzYg2r4POoOEvOIsdWfEWy7D6jBpvHoiIqL+xeQjBUwWAwqHulE41A0AiMfiOHbwlDpvZG/1Iez4SDnoLttr675VUy5DzrOyxZeIiAYUJh8a0Ol1yC3OQm5xFkbdVAghBFqPtyWKWJWE5KtNIUAA1iyjWsDqK3fBU+yAni2+RESUwZh8pAFJkuDMscKZY8VV470AgPbTUTTva1EKWYMRbHlnH2LROAxGXXeLb0CGd4gMk5X/G4mI6NulSckHk490ZbYZUTIiByUjEtNYO+M4sr9V2RkJhrH73wexdU09JAnIKXSouyP+gIstvkREdEla385n8pEh9AYdvEOUnY6xtxZDCIHwodNK3UgwjMbdx7DrrBbfriJWX7kL2V4bW3yJiChtMPnIUJIkIdtrR7bXjsrr/QCUFt+z60b2Vh9SWnztBrWA1RdwIa+Yp/gSEZF2mHwMIHbZjPJr8lB+TXeL76H6FvVWTfWaenS2x6A3KmfadCUj3jInzDae4ktENOCJ9Kj6YPIxgJksBhQNdaMo0eIbi8Vx7MBJNRnZsymEbWsbAAnI8TuU2zSJWzVZbovGqyciooGKyccgotfrkFfiRF5J9ym+kSNn1Ns0B74+gd0bDwIAHG4zfOUu+APK7ojbx9HwRESUHEw+BjFJkuDKs8GVZ8OwScopvqdbOtCcOMU3VBtB7bbDiHeNhi/r3hnhaHgiIuorJh/Ug81pQtmYXJSNyQUARDtiOFzXPW9k29oGRNuU0fD5JU41GfGWy7DYWTdCRJTO0qTkg8kHXZrRpEfB1dkouDobwNmj4ZVk5Ostzdj+L2U0vNtvV4tYfeUysnIsmveSExHR+bT+0czkg3ql52h4pW6k9VgbQsEwmmojaApG8OWnTQAAu8us7oz4K2S4/Q7oWDdCRDToMfmgKyJJEpweK5weK66eoNSNtJ2MItRVNxIM4z87ahCPCZishsTOiDKJNa/EyXkjRESDEJMPSjqLw4ghozwYMsoDAOjsiCXmjYTRFIxg24cN2NK+D3pD1zk1SjLiLeM5NUREgwF/0lO/M5j0KLgqGwVXddeNHE3MG2kKhrHnsyZs+7BBPafGH3DBF3DBX+GCzWnSePVERAMQaz5osNFdYN5I+NBpNRmp33UUOxPn1Mh51rOSERlOj5VFrEREGa5XyceLL76IF198EfX19QCA4cOH44knnsD06dMRjUbx+OOPY82aNdi3bx9kWcYtt9yCZ599Fn6/vz/WTgNEj3NqvqN8rZw80Z64TaPUjXy1OQQIwCabeiQjLGIlIuqFTGy1LSwsxLPPPotAIAAAeP311zFz5kzs2LEDhYWF2L59O379619j9OjROHHiBH7+85/jzjvvxNatW/tl8TRwObLNqLguHxXX5QMA2k5F1eFnTTUR/GdVdxGrt0xWC1nzS50wmDj8jIjoUiSN77tIQlzZyBG3241ly5bhJz/5yXn/Vl1djfHjx6OhoQHFxcWX9XwtLS2QZRmRSAROp/NKlkYDWHcRqzIavrk2go62GHR6CbnFWeqsEV9AhtXBuhEiIkDpRnzlsU8x/b9HomxsblKfuze/v/tc8xGLxbBy5UqcOnUKEydOvOA1kUhEGeHtcl30edrb29He3q6+39LS0tcl0SByXhFrXOB40yl1LHxw6yF88ZEy/Czba4O3XJk34gvIkHNZN0JEpKVeJx+7du3CxIkT0dbWBofDgX/+85+orKw877q2tjb88pe/xOzZsy+ZAT3zzDN46qmnersMoh50OgmeQgc8hQ6MvLEQANB6vC0xa0TZHflqk1I3YnWa4O+axBqQ4Sl0QKfnvBEiGvhEmhR99Pq2S0dHBxobGxEOh7F69Wq8/PLL2LhxY48EJBqN4u6770ZjYyOqqqoumXxcaOejqKiIt10o6dpPR9G8r0XdHTlU14JYZxwGsx75pYl5I+Uu5Jc5YbKwEYyIBp4zJzvwP499hukPjlTP8EqWfr3tYjKZ1ILTa6+9FtXV1fjd736HP//5zwCUxOMHP/gB6urqsH79+m9dgNlshtls7u0yiHrNbDOiZEQOSkbkAABi0TiO7G9NdNREsLvqILZ+UA9JAjxFWT3OqbG7+DVKRJQsV/znnRBC3bnoSjxqamqwYcMG5OTkXPECifqL3qiDt0yGt0wGbkOPeSOhYBj1u4+p80acHotaM+IrdyHba4PEFl8ioj7pVfKxcOFCTJ8+HUVFRWhtbcWKFStQVVWFtWvXorOzE3fddRe2b9+O999/H7FYDM3NzQCUjhiTiR0HlN4uNG/kVKS9R0fN3upDEHEBs92gJCPlSpsvz6khooyQHiUfvUs+Dh06hHvvvRehUAiyLGPUqFFYu3Ytbr31VtTX1+Pdd98FAIwZM6bHx23YsAE33nhjstZMlDJ22YzAuDwExuUBADraOrtbfINhVK+pR2d7DHqDDnmlWWpC4i2XYbEbNV49EVF66lXy8corr1z030pLS3GFI0OI0p7JYkDRUDeKhroBnHVOTW0EoWAEX28JYfu/GgAAbr9d3RnxBVzIyrGwxZeICDzbheiK9Din5mblnJqWo21org2jqTaCpmAEX37aBACwyyZ4E3Uj/oALOQV2tvgS0aDE5IMoiSRJgpxrhZxrxdUTfAASo+FrlbqRUDCCTW8HEe8UMJr1yB/iVOeN5JeyxZeI+le63KDgTzqifmaxG1E6yoPSUR4AQGc0hiMNrYlbNWHsXL8f1e/XQUoMSuvqqPEFZNhltvgSUfJpfQeYyQdRihmM+sRuhwuYVgIRFzjRfFrdGanfeRQ715/V4queU+NCdj5bfIko8zH5INKYpJPg9tvh9tsxfHIBAOBUuF3dGQnVRrD382YIAbb4EtGAwOSDKA3ZXRdo8a3rHg1/fouvcquGLb5ElAmYfBBlAJPFgKJhbhQNu1iLbzO2/0s5xdftt8NbLquH57HFl4i6dI3E0Pr2LZMPogz0bS2+oWAEe9jiS0TnEHHlv1r/QcLkg2gAYIsvEV0OdeeD3S5E1B/62uLrr3DB5uRZTEQDkYjztgsRpVBvWnzlPCv8iWv9FTKcHqvm27REdOW6hoxp/e3M5INokLpQi+/JE+0IBcNoCoYRCobx1eYQIJS6EV+FS01Icvx2zf9yIqLe677twp0PIkoTjmwzKq7LR8V1+QC660a6kpHPVtYgHhMw2wxKR00iGckryYLewCJWonTXfdtF23Uw+SCiizq3biTaEcPhuhY1GVHnjRh1yC91wl+hFLF6y2QWsRKloe7bLtz5IKIMYTTpUXB1NgquzgbQPW+kqSaMppowdv/7ILauqVeLWP0BF3wVyg6JNYtFrERa45wPIsp4Z88bGXNLMYRIFLEm6kb2fXEE/7d+PwDAlW+Dv8IFf4DDz4g003WqLQtOiWigkCQJbp8dbl93EWvr8bZEMqK0+O75TBl+5sg2K900iWTE7WMRK1F/i8dZcEpEg0CW24Ks8V5cNd4LAGg7GUWotjsZqd12GPG46D40LzGJNbckC3pOYiVKrsTOh463XYhoMLE4jBgyOhdDRucCAKLtMTTXRRCqURKS6vfr0NkRh8GoQ36ZM7E74oK3TIbRrNd49USZTagVp9qug8kHEWnKaNajaKgbRUOVQ/NisTiONLYiVKO0+O6qOoCtHyhFrLlFDnXeiD/ggsXBE3yJeoNnuxARXYBer4N3iAzvEBljbyuGiAscbz6FUDCCphrlNs3/fawUsWb77GrNiL/ChSy3RePVE6U3nu1CRHQZJJ2EHL8DOX4HRtygFLG2HDujJCNBpcX3y8QJvg63WdkVqVDeXPk2zf/CI0onPNuFiKiPnDlWOHOsuPq/lCLWM60dajISCoZRs/UwRFzAmmVUExF/hQs5fofmP3SJtMSzXYiIksSaZULZ2FyUjVWKWDvaOpWx8DXKvJH/rA4i3qmMhfeVy/BXZMNf4YKn2MGOGhpUeLYLEVE/MVkMKB6eg+LhOQCAzo4YDtW3qJNY//e9feiMxmEw6+Erc6o7I3mlThiM7KihgUvd+eDZLkRE/ctg0qPgqmwUXKWMhY91Kh01XTsjOz7aj8/frYPeoEP+kEQyEnAhv8zJM2poQBEcMkZEpA29QQdvmXIA3jXTShCPCxw7eBJNe5VkpOuMGp1OQm5JllrE6i2XYbGzvZcyF892ISJKEzqdhNyiLOQWZWH01CL1jJqu2zR7qw9hx0eNgATkFDjgr3ChoMIFX8AFm5MH5lHmYMEpEVGaOvuMmhE3FEAIgZajbeptmobdx7BrwwEAQLbX1j34jLNGKM3xtgsRUYaQJAlyrhVyrhXDJvkAACdPtCMUDONgYndkT2LWiNNjgT/gUhKSChfkXKvmP+iJunQXnDL5ICLKOI5sMyquy0fFdfkAzpo1UhPGwZoT+PrzZkAAdtmkdtP4Klxwe3l6L2mne+dD23Uw+SAiSoJzZ420n+lEKDH0rKkmjE/fqkE8LmCxG5WTeytcyCtxQqdnIkKpEz50GgBvuxARDUhmqwGlIz0oHekBoJzee6gugoM1YYRqwtjyzj7EonGNV0mDkc4gQW/SdtAHkw8iohQwmvUoHOpGYdfpvdE4IkfOdB9xTpQiFrsRRpO2w/SYfBARaUBv1MHtt2u9DCJN8FADIiIiSikmH0RERJRSTD6IiIgopZh8EBERUUox+SAiIqKUYvJBREREKcXkg4iIiFKKyQcRERGlFJMPIiIiSikmH0RERJRSTD6IiIgopZh8EBERUUox+SAiIqKUSrtTbbuOl25padF4JURERHS5un5vd/0ev5S0Sz5aW1sBAEVFRRqvhIiIiHqrtbUVsixf8hpJXE6KkkLxeBxNTU3IysqCJEkXvKalpQVFRUXYv38/nE5nileYuRi3vmHc+oZx6xvGrW8Yt75JZtyEEGhtbYXf74dOd+mqjrTb+dDpdCgsLLysa51OJ7/I+oBx6xvGrW8Yt75h3PqGceubZMXt23Y8urDglIiIiFKKyQcRERGlVEYmH2azGYsWLYLZbNZ6KRmFcesbxq1vGLe+Ydz6hnHrG63ilnYFp0RERDSwZeTOBxEREWUuJh9ERESUUkw+iIiIKKWYfBAREVFKpXXy8fTTT2PSpEmw2WxwuVwXvObhhx/GuHHjYDabMWbMmPP+vb6+HpIknfe2du3a/l28hpIRt7MFg0FkZWVd9LkGimTE7ZtvvsFNN92E/Px8WCwWlJWV4fHHH0c0Gu3fxWsoGXGrqqrCzJkz4fP5YLfbMWbMGLzxxhv9u/A0kIzYtbW1Ye7cuRg5ciQMBgO+973v9eua00Gyfsbt2rULU6ZMgdVqRUFBARYvXnxZ55JkqsuJW2NjI+644w7Y7XZ4PB489NBD6Ojo6HHNP/7xD4wZMwY2mw0lJSVYtmxZr9eS1slHR0cH7r77bvz0pz+96DVCCMybNw+zZs265HN9/PHHCIVC6tvNN9+c7OWmjWTGLRqN4p577sHkyZOTvcy0k4y4GY1GzJkzB+vWrcM333yD559/Hi+99BIWLVrUX8vWXDLitmnTJowaNQqrV6/Gzp07MW/ePMyZMwfvvfdefy07LSQjdrFYDFarFQ899BBuueWW/lpqWklG3FpaWnDrrbfC7/ejuroaf/jDH/Dcc89h+fLl/bVszX1b3GKxGGbMmIFTp07hs88+w4oVK7B69Wo8+uij6jUffvghfvSjH+HBBx/E7t278cILL2D58uX44x//2LvFiAzw6quvClmWL3nNokWLxOjRo897vK6uTgAQO3bs6Je1pbMriVuXX/ziF+LHP/7xZT3XQJGMuJ3tkUceEd/5zneufGFpLtlx++53vyvuv//+K19YBkhW7O677z4xc+bMpK0r3V1J3F544QUhy7Joa2tTH3vmmWeE3+8X8Xg8yStNLxeL25o1a4ROpxMHDx5UH3vzzTeF2WwWkUhECCHEPffcI+66664eH/fb3/5WFBYW9ipuab3zkUx33nkn8vLycP3112PVqlVaLycjrF+/HitXrsSf/vQnrZeSsYLBINauXYspU6ZovZSME4lE4Ha7tV4GDVCbN2/GlClTegzXmjZtGpqamlBfX6/dwjS0efNmjBgxAn6/X31s2rRpaG9vx7Zt2wAA7e3tsFgsPT7OarXiwIEDaGhouOzXGvDJh8PhwPLly7Fq1SqsWbMGU6dOxaxZs/C3v/1N66WltWPHjmHu3Ll47bXXeEhTH0yaNAkWiwUVFRWYPHkyFi9erPWSMsqqVatQXV2N+++/X+ul0ADV3NyM/Pz8Ho91vd/c3KzFkjR3oZhkZ2fDZDKpMZk2bRrefvttfPLJJ4jH49i7dy+ef/55AEAoFLrs10p58vHkk09esAD07LetW7cm7fU8Hg8eeeQRjB8/Htdeey0WL16Mn/3sZ/jNb36TtNdIhVTHbf78+Zg9ezZuuOGGpD2nFlIdty5vvfUWtm/fjr///e/44IMP8NxzzyX9NfqTVnEDlOLTuXPn4qWXXsLw4cP75TX6k5axy2RaxE2SpB7vi0Sx6bmPp7Nkx+1Cn7sQQn18/vz5WLBgAW6//XaYTCZMmDABP/zhDwEAer3+sl/HcNlXJsmCBQvUhV5MaWlpv65hwoQJePnll/v1NZIt1XFbv3493n33XfWXphAC8XgcBoMBf/nLXzBv3rykvVZ/0urrraioCABQWVmJWCyGBx54AI8++mivvjm1pFXcNm7ciDvuuAPLly/HnDlzkv78qZAOP+MyUarj5vV6z9vhOHz4MACc99d/Oktm3LxeLz7//PMej504cQLRaFSNiSRJWLp0KZYsWYLm5mbk5ubik08+6dXrABokHx6PBx6PJ9Uv28OOHTvg8/k0XUNvpTpumzdvRiwWU99/5513sHTpUmzatAkFBQUpW8eVSoevNyEEotFoRrXwaRG3qqoq3H777Vi6dCkeeOCBlL52MqXD11wmSnXcJk6ciIULF6KjowMmkwkAsG7dOvj9/oxKDpMZt4kTJ+Lpp59GKBRSf0euW7cOZrMZ48aN63GtXq9Xfxe8+eabmDhxIvLy8i77tVKefPRGY2Mjjh8/jsbGRsRiMXzxxRcAgEAgAIfDAUAp6Dt58iSam5tx5swZ9ZrKykqYTCa8/vrrMBqNGDt2LHQ6Hd577z38/ve/x9KlSzX6rPpfMuI2bNiwHs+5detW6HQ6jBgxIpWfSkolI25vvPEGjEYjRo4cCbPZjG3btuFXv/oVZs2aBYMhrb/d+iwZcauqqsKMGTPw8MMP4/vf/776F6nJZBrQRafJiB0A7NmzBx0dHTh+/DhaW1vVa75thk+mSkbcZs+ejaeeegpz587FwoULUVNTgyVLluCJJ57IqNsuvfFtcbvttttQWVmJe++9F8uWLcPx48fx2GOPYf78+Wrt39GjR7Fq1SrceOONaGtrw6uvvoqVK1di48aNvVtMr3t0Uui+++4TAM5727Bhg3rNlClTLnhNXV2dEEKI1157TQwbNkzYbDaRlZUlxo0bJ/76179q8wmlSDLidq7B0GqbjLitWLFCXHPNNcLhcAi73S4qKyvFkiVLxJkzZ7T5pFIgGXG72HNMmTJFk88pVZL1vVpSUnLBawaqZMVt586dYvLkycJsNguv1yuefPLJAd1mezlxa2hoEDNmzBBWq1W43W6xYMGCHu3IR44cERMmTBB2u13YbDYxdepUsWXLll6vRRIig/aCiYiIKOMN+FZbIiIiSi9MPoiIiCilmHwQERFRSjH5ICIiopRi8kFEREQpxeSDiIiIUorJBxEREaUUkw8iIiJKKSYfRERElFJMPoiIiCilmHwQERFRSjH5ICIiopT6f1/i34n0mBcVAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "696 still has an enclave\n",
      "696 was also in the triage list\n",
      "the total and enclave pops for 696 are 752831 208\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "894 still has an enclave\n",
      "894 was also in the triage list\n",
      "the total and enclave pops for 894 are 732091 165257\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "898 still has an enclave\n",
      "898 was also in the triage list\n",
      "the total and enclave pops for 898 are 726413 24669\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1349 still has an enclave\n",
      "1349 was also in the triage list\n",
      "the total and enclave pops for 1349 are 687912 133962\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1386 still has an enclave\n",
      "1386 was also in the triage list\n",
      "the total and enclave pops for 1386 are 741359 7114\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cantFill = list()\n",
    "for t in popHDlist:\n",
    "    if t in enclaveOnly:\n",
    "        print(t,\"still has an enclave\")\n",
    "        cantFill.append(t)\n",
    "        if t in triageList:\n",
    "            print(t,\"was also in the triage list\")\n",
    "        unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "        print(\"the total and enclave pops for\",t,\"are\",np.sum([unitPop[u] for u in HDunitList[t] ]), np.sum([unitPop[u] for u in enclaveList]) )\n",
    "        for u in HDunitList[t]:\n",
    "            plotPoly(unitGeom[u], 0.5)\n",
    "        for u in enclaveList:\n",
    "            plotPoly(unitGeom[u])\n",
    "            plotCenter(\"e\",unitGeom[u])\n",
    "        plotPoly(MAP)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "750fb250-e608-477a-924e-b21882d3d060",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "above should have cleaned them all up, but it didnt, so we will run the MUSTFREE code again\n",
      "this code will solve large enclaves so HD and complement are contiguous for 6 HDs\n",
      "working on HD 625 cantFill 0 of 6 .Time is now 0\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 0.99292 0.14958\n",
      "CCB cluster 0 = unit 1513 with pop 47669.0 now has use of 0.9957586773061896\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"above should have cleaned them all up, but it didnt, so we will run the MUSTFREE code again\") #RUN ONLY IF NEEDED; e.g. AZ\n",
    "\n",
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug = False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %10 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for eL in enclaveLists.copy():\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border enclaves\" )\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find oop end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debug:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debug:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "7b5fe263-e765-4e59-be03-ed51c30ec740",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final check -- any more disco's ?\n",
      "working on HD 300\n",
      "working on HD 600\n",
      "working on HD 900\n",
      "working on HD 1200\n",
      "working on HD 1500\n",
      "out of 1652 total HDs, there were 1652 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "print(\"final check -- any more disco's ?\")  #SKIP IF WE DIDN'T NEED TO RUN ABOVE BLOCK\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "1e983c03-777a-4e81-bed0-34a620175f83",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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LueSSS6i0VfmXfe12e6vGodNocXncAFiLCzFEhRE3JIUB10wJ2K/70z3xJJoZcM253n2tVo7fUkjckBR0Wwx0G9HXf0zV8WLUx4QvjEDQFEKwtALhwSIQhAYSUqMuZbFR4W3qZ/rNvyPGVsLs2bOx2+0BFpXW4Fbqcq9IWoUDBw6wZs2aBvtNmzaNN954g0suuaTJXDD+fmRZ+MsJBM0gnG5bicjDIhB0PsH6HRrDI/whz/fee2+bj29M4GzcuLFBCPMXX3xBTEwMs2fPZubMmcyZM4e+ffsG7OMLfZY0Mh6XB9uJCoamD+HB+//U8LxtHqlAcOYgBItAIOgynKxXZFluIB5cLleL/Tx86SS/uFi4cGG7xyPLMpP698fhcOB2uxvdftVVVzWaC+bksRvjLKCT8TgcKE4XRTuyAvoqOV6FwSSM4oKzFyFYBAJBl6K+PomPjw9wnm2qXtDJeOq5ilgslnaPRVEUfsk8GtDmSwyXmprKiRMngDorSv2kcYWFhXz00Uf+46qqqsjJP054j27owk0YIuoioSpO1OCocZHYJ7LdYxUIujpCrrcCsawsEJw+Nh0twe5u3Pm0xuFGp6mzs7TFR6Q+miBO1dz1QqAfeeQRTCZTwPaXXnrJ78xrt1r5f089RU1uLkadjm1bt2I2Glny17/y7N//jqSqFO7fj72igvIaKwDVFQ4qimz0GizS/wvOboRgaSXChUUgOD3Y3Qrn9o9v1b4LFy7k6NGjjdYLag4liJOQLUePAODxePA4nbhUlRM7d+CqrsbhsiPJEorbRUXmzyiKQrXNxqHSUpJ79cLj8bBv3z5UVSU+KYm0uDgSBg5Es2sX+rg4HDY3BUcr6DuiW/AGLBB0UYRgEQgEIUWlvWUfFB++ekH1mT9/fovHSaqbvGO72b39f1w48zYkqf2WVE+9A+1OJ+GRkcQPG472l60U5ZURExODrMjk213Ya6c+WRVWVOCqq67i8ccf95YAMIZz/zP/wu2wse+RR3ArWnJ2l9BvtBArAgEIHxaBQBBinI4l2IToSDxE0X/YLHR6E2Zz28Ki6+OuNddIkoTT5SI/P58vvviC3Nxcf40hSZJwdksiIswMQM+IcIqqqgHQ6g2oqooBN8PitXz84t+QJAmdyUS/Ud2QRIiiQAAIwdIqVBFMKBCcNiKMHWf4TU1NZenjjzJyxAjeefttNv30E8ePH8fjaRjh01qUWoWl1vt/y5YtqKqKXq9DURSqqqr48X/f+perFI+H8vw8XG4P5rBwJEli165dzJw5kyuuuAK9Xo9WKyPJQqwIBD5OSbAsXboUSZJYsGCBv01VVRYvXkz37t0xmUxMnTqVPXv2NNvPG2+8gSRJDf5am3XydCAmOQLB6aEjLQpul5MjRw7x9N//H1OmTGH27Nm43W569+7dIed1uVxUVlah0+k4sms/4H19mzZtQqfR8sWe42hkCVVVmTx5sj/0ecCAAYwYNyno4xEIujLtnsps3ryZV155hWHDhgW0P/nkkzz99NO88cYb9O/fn0cffZTp06dz4MABIiIimuzPYrFw4MCBgDaj0dje4QkEgi7K1uwyiisdTO4fR7eI4F0DVm89hM2lEKNzoxQf8vu+SJKEoigsWLCAZ555JmjnA1BVCYfDAYAxzISt2gZ4w6979uxJWeUhThR6w7IrCkvY8N4XoKpYi0vxZGcFdSwdwbGyGn44WAx4I68kSUIjScgyyJKELEloZAlZqnvu21ZRmE/h/l0MjjOQ7Eump6ooqoKqKKiKiqooKIqConhwHc0k0RSBwWDwziAlkI1GwiZNQhb3irOCdgmWqqoqbrjhBl599VUeffRRf7uqqixbtowHH3yQK664AoA333yThIQE3nnnHe64444m+5QkicTExPYMRyAQnEEsuCANgE+3HefS4d3R1otBLrTa2ZFbzvi+sViMujb1W1RRTYTZSPeBY7CeOE5SbbskSdRUlPPhBx8E6yX4UVWV7t27k5eXR0RMNAlx3cjJycHlcnHk6FG0x3LxxiCqlNkqmXDtLKxWKwW/KqZHbNMTvFBhwXvb2ZJddgo9RDNk+x7Oe//NVu2dVFbJiJyigLbYX/+abn9oe7ZiQdejXYLlzjvvZNasWVxwwQUBgiUzM5OCggJmzJjhbzMYDJx77rmsX7++WcFSVVVFSkoKHo+HjIwMlixZwogRI9ozvKAj8rAIBKcP39LMrGFJrN5XhFmvodrhxu72kBBhpGeMmb15VjSyxJjUmIBjU1NTWbBgQcAydUZGBnPmzKH/uXP82WWtJUXkb/0aVG9NoIKSUixmc9Bfi6qqjB07ls8++4wTuXn+dp1Oh8vlwu1w+tvsdju7d+9m0qRJeDyexroLKVRV9YuVocmRdIswoKgqHtW7zaOoKKqKolDbrqLU25ZXUEyZoqdcF0l8Sm9/v5IsI8sykiwjSTJ5B/f5t9XodZjHjwfAlZeHKycHd1Hh6X3hgk6jzYLlvffeY+vWrWzevLnBtoKCAgASEhIC2hMSEsjOzm6yz4EDB/LGG28wdOhQrFYrzz77LJMmTWLHjh2kpaU1eozD4fCbWsFrYu1IJJGJRSA4rRi0Gi4akojd5cGglRv4mGzLKeNgYSX9E1pvifBlxh14/Z2gM2KtsqGqKuFhFkrKS4L9EgBvPaGTaax8QGFhIcOGDSMiIoLo6OgOGUswKamuE1vFVQ5W3DkJuQ1Owq9+9B2PbbGhM0cwb+k/mtzvmwV3sjvfe//oO2wEKY8/5T3/G29Q9LcnUD2iwvXZQpucbnNzc7n77rt56623mvUvOfnCoqpqsw5t48eP58Ybb2T48OFMnjyZDz74gP79+/OPfzT9JV66dCmRkZH+v549e7blpQgEgi6CUaepu36UHoXN/4LDqxnh/AXnL+9wPNubuG3fmg9xOmwU5BwEwFZl5cCW1bicDn8Ez7Rp01i+fDnbD+YwcOhILpp1CQAR4R23/NKa2kY+VFWlsrKSgQMHsujWWztsTMEgLtzAvAkpAORX2Hnim/1tOl6n9d5+WrIlSbJ3v/4xCZxXK1a87bUZjZXQt0YJgkObBMsvv/xCUVERo0aNQqvVotVqWbt2Lc899xxardZvWfFZWnwUFRU1sLo0OyhZZsyYMRw6dKjJfRYuXEhFRYX/Lzc3ty0vpU2IJSGBIEQwRELyKOh3AfS7gMEX/Zr8Xd+xZ+M3uBQFnU6PwWBi+xevcGT7GhL7DEf1uCg4uIWaoiyu6+9gwsghzJ49m8LCQoYOHQrAseM5nfzC6lBVlR9//JHHX3+9s4fSIo9cNoQn53oDL15ee5TfvvVLq4/Vab2Cw9PC9dUnWFT1JEtKrW+TsLCcPbRJsJx//vns2rWL7du3+/9Gjx7NDTfcwPbt2+nTpw+JiYmsWrXKf4zT6WTt2rVMnDix1edRVZXt27eTlJTU5D4GgwGLxRLw15GIsGaBIATQm8FZ7X8qyTKjZ/8aWatn8Llz0Wh1RHXrQcas2xlyzqVExsQjaQ0k9h/NhHgbQ256gmd/fynFhfn06NGDsWPHeqOETr4ZhgRdY6Z09eieDO8ZBcBXuwv4cEvrJo96rdcjwaM2f3GVa4WJLwmfD0kjLCxnG23yYYmIiGDIkCEBbWFhYcTGxvrbFyxYwOOPP05aWhppaWk8/vjjmM1mrr/+ev8x8+bNIzk5maVLlwLw8MMPM378eNLS0rBarTz33HNs376df/7zn6f6+gQCwZmE1giuhvmZBo0+D2i6erMkSQyedh0AyefdSs4nf/WbTmVJRpXUBjfE9iJJkn8J6mzh499MoN+DXwHwx492YtZrmTWs6Qkn1FlY3M34B3ocDnyV3NSTC0DJwsJythH0lJL3338/NpuN3/3ud5SVlTFu3DhWrlwZkIMlJycHWa4z7pSXl3P77bdTUFBAZGQkI0aM4IcffmDs2LHBHp5AIOjKSBIUHwStwftc1oCk8f6fMLhV1ZtlQxhJsx5AufcNHnnkEVRU9Dod9npO/G2hW0wkRaUVyJLElZfN4sMVnwMQHh9NdXFFw6WMMxCtRmb1vVO44OkfALjzna3ER0xgbO+YJo/R6byfi9KEheWjW24gu6bC/7xJC0sXiKgSBIdTFixr1qwJeC5JEosXL2bx4sWtPuaZZ54JesKmYHJ2zZUEghBnzG2A6rWQqB7vkoCtDAr3tLp6s8ESR2xUBBV53sigU/mNl1Z6l6gUVeV/K1ejkTV4PB5s5ZVYLBYqKsrb3qmqUl1eTu7bb9Pjuuv8fhyhTL9uEez4ywyGP7ISgKtf3sDhxy4OyKNTH4NvSagJC8vxyjK/n4qkqvRMD7TuU+t0qwbJMiZomc6+F4pqza1EuLAIBCGCVt+wzVYKBkubqjenpfVl58FsJEnG6Wx9JM/JmMPMWMut9OjZk6tefoBnL7kbtDIxPXtTkpvVrj49ikKpVsthWSZZVbvM9SfSrCPRYqTA6l22q3Z6iDQ1Llh8FpamBIuv9cpbfkf3iZPQWyIDt/uEkLCwnAZC4xsY+rJdIBAIWsJRBYaWQ5NTU1NZtmwZAH/6y2L0Oh0ej/uUlm2MWh0S4KypRM21oHgUTMYwbr5yDh8fOMLA6Re2uU9Zlunepw/nXXcd8klLWqFOYaVXrIzrHUOkqelsxHqdd76sNHEb8t0i9RERDcQKICwsnUBnu2YJwSIQCLo++jDI3QjFTadCOJlhQzKIjYkiPDwcs9mMRts2g3N0ZCSSJFFSWgaSRKm1mo+X/hVQ0Wm1LF++nD/OmMaUvr1b7Ks+Wo2GqKgoqqurW945BDHWOtM+OGtQs/vpW2lhUdyNV9IWFpbTR6hEyQrB0grONo9/gaDLEdMbBl8O5U1n1C7d+hUem5Xy7V+T8/ItHF33IcawCCRZi93haHM6/ItmXgx4C/mpqorb5WJC/zSQJPQGA4MHDOTokaO89Wbr6uSA1wfwjusv5ejRo9x3331tGk+o4Km9XsaGG5rdz6DzLu15WrCwKE19LsLCctYhBEsr6ciS9wKBIEhUFUFZFpTnQMVxsOZjLzyKrfAotoPr0JgsRGVchDJtEev3FzFr9qXYaqowGY1cPW9+q5xbZUlGK8u89977qKpKcnw8BoMBg8HAqEHpWEwm7JVWFv35z/Tt15fkHj2QJAlzpNeao23CkiPLMhqNhpiUwZjNZmbOnNls8EKoovrDxZvfz2dhUaQWBIuwsIQMnT15F4JFIBCcOaRMAo8bXDZwWHFXFpG9YSXVOXuIGHW5v/hhYo8edE/uzZKH/4rZbKa6upqVKz4jNcWbal6SJCRJZtz4czCZTP7utVotKipGo4mn7vwtRqOR48XFKIqC0WhEVRUsYWG4FYWLZ80kKyuL9PR0dFotLlsN9/5pIau2rGLitIkYTV4Lg08k9U3rT+++acgaTYNQ7K6Cw+3BVZu6VtPCJE+v9/q3KJKGZ9/6usF2qfbeqLgbFyTVGzcBwsJyOgiV6boQLAKB4MwhOgXi+kH8AOg2COIHUWNMJm7MJVjSxvgTyxlNJkZOmsyqTz7C5XIRGRnJX//6V84fPQDwLvOAyoEDuwOu1jqtnqH9h2OQNVQXlBEbGYmiKN5dPB7kqGg0skxMTAwLFy4kLS2NjIwMuicloTMYOHr8IIePZ/Lj6h955T8fkZSUxkWX3Eh8QhITpl3EDz9tYPHixciyjLsJy0KoUmFz8X/vbPM/tzTjcAsQG13nJP3qzsoG231v++b3l+MoL2+w3ZmVBYCnpGOKVgpCDyFYBALBGYtWryc6sbv/ua/44bp16yg4UcwzL72CRqPB7XJxZN8erps+CfCGFauqSo/kHrjqhzxLKjMvv4jS6koe+eR9jhcWotPpiIuPp9pu59NVK8kvKaG8pISc7ds5evgwBXv2kp2bi8Nmx1mtoq2OprrGRny3KOLiTCRZjJiNekb0TyExti4apitZWf69JYfhD69k1d5CAAYmRmDUNT/+iDAzD4wyNbndHeciYeQJCijn0CcfNNyh1oIT++tft3/ggjbR2d6cQrAIBIIzGkmjoUf37jz0xz9w5bQpnDNpErNnz2bkyJFIskR8bAxmswlTZDRqWE3AsdXFJQEXSZvNRkFBARqNhjCTmTCzGa1Ww+9+dwVRUeHs2LEVWSthczr5Yv16JI2Gb7d5rQ5ajcyEESPo168Hq3/agEGvR6519PAtVdWnq1hYVFXllc2Byfmemju8Vcem9ewGgLZeWLm1LJdVn1zOoGuOkjSmmPgBpfS/6rqGB9f6rsjmpkWPIDiEig+nSBwnEAjOaFKGZqDV64lN7knfIcNYcu9dvP7KS0yedgHnz7iQN954gyFDh7F8+XJiu/8qoBZQZkF+QF+SJPHOO+/gdrvpNTAVjUZD5tHDmM19SEzsgaqq7NmzB4DSsjIkSaJbXCLHjh9DVVVUVeWcEaP9/blcXutNYzWQjh071tFvTbuw2+1s27YNh8OBqqqsXbuWC4Eqg54vHQNxhIVhMLfu1uJwe4WKBg9lJ06wd/tqKuxLMUTVhXQPTk1FH9Ewx44/d04TTruC4NPZAbNCsAgEgrOG6KRkIrsl0qtnD9R6N7oZM2awbds2/vzHJ1BVFVmWURQFrUbGXVtcLzY2FqvVynnnncd3331HcnIyX3/9NSaTkY8++giNRsOcOXMoKc6juMTKgw8+yJWzr0dC4sbbrqK4uLjRwozjR53TqhpIHU11dTUfffQRVqvVL9jq/+97XFFR0ejx4ZKTeLma7GoDF/1jHeePSubRqf1JaCa82VkrWCRJ4tnnnycldQe9UgLzz8hSE+9D7eciNZH6XxA8QsO+IgRLq+hsVSkQCFpHamoqCxYsYMGCBf62jIwMyus5bcoaDZKswe2sK3b44IMPBhTX8z1216sE7Fuiycnzig7fDdxsMrJz505iY2MpKiqivKIakNi+6wjXX6mn/9BUXC4XqampLF++vFFR0lgNpP379wf1vWmJrKysRusuNYXFYmHAgAHIssymTd6InbFjk8nZ6kCxeVj1Yw6rNuTSu180o3pFc/+E3oQpEsdyKrDZXew7WsYzv+QBIGskkCQ0WmeD80TEDGnQBoDv8+oCdZYEwUEIllYSIkt4AoGgHdRf5gHQaLXYampYtmxZkxaDk/Htt3/PblRFofCw9+YeExNF7rECsrOzefvtt4mMtmC3e4iM68b+ag1bv93L4SNHOfeK+YwKj2PmxbOIjokKKMzYWA2kSZMm0a9fv2C8/Fbhe38SExO5+OKL/X4L3hDvuscABoOBuLg4/7Er9h4ksbKMtG4R/Pync3h43WG+3nKM5KpcHj+ylIqt4/nvm1WsNCWyOWpkgHULVNI0xVx24QwKrfv8rfa8VEw7EtlV8zPbVszGkJZG0rCxpI2ZQbglti6cWQiW04bayW63QrAIBIIzlrWllVR5FDRGE5uOZvF9iRUAm9tDubUSvdHY5j5VRUGWJQ7l5fLR08/gsjlQFTc6nYY7b5lFlsPD95/9wG03ziE6vIKHnngInU5Lcs9o/v3OS2TvKSFlcCzgLcy4/tutQX3Np4rRaCSlNh9Na/HN5zJt1fx6/d/JqdiCJU1GqSrDkXMtQ8KGMSQMbNnPUSFHkhfZnxiNzHCTHZ1zLxGyk/fWrGDGuC3+Ph2ubpTkTWfML094G747AnzNId0jHB/SjZTjLrTQJSpZd3VCZcIuBItAIDgj8HgcKIoTh/MEJSU/AFCWt40wjYQxOYoPX3ieeBTuuOMOqspK0WhkHLaaFnptHFWFsIgIfvXwYmpqavB4FMxmM25HKXNuuwpPKf7lnYcfeYTthw6TYmo+VX1XRvZUAbD54FIKzXn+9nIN9LMP8z/Xyjoe2fBvxm3fAcDKr75g/SbvMpDJERjtU7zrcsKV3WRdPBSNRot6NIfInDIiqxT6bivy71fmstJy2UtBUBBOt6FPZ5vBBAJBy5SUrEGj0SChITZ2CgAjtL0pq3qSuZdfy+G9R3n11VdZsWIFiYmJlJZVUF7W3qRjKidOnCCtTyq5eY5ap1SFp176hrj/buXE8bob6nclVvbdNA9jrXNoiExWg4pBrQIMgAdJ143ZaTcSZ4rF5XGy/MT73FR8DWVOGwllcUTp63LNJMTHcYVjHMcMJzDMScYoT8AoHSM2LIPJS4ehN1wdcB5VVTm8aSUHPnkD8487Ca9ROBGr0Ov0vtyzDilEvrVCsLSSUPnABAJBIIVFX6LVhKPVWejWrTvFxXb/tmgpkuK8MixhEcTFxXHRjefztwefom/3NNzu9qd097nDHM3OxWg0Yrc7/AnmaqxVDfY3nhTJoqpqyOS2CAbG2tdycb+ruGvar9Bp6m4tX1XsofL229ECA/VGBuysy4aLqhKjhuOQHIzJOL/F80iSRNr4C0kbfyHXf3E9u4p38Y+kuBaPE5wZiMU/gUDQpdFqwomNnUJM9ISATLa7d+8mMTHRH/GjlbUMjs9g3JhxOBUXCbFJp3xujUZDnz59AHD5E73VCZHVJVZsJ9W6kTQSqnJmWW19Vuhe4TEBYgXg4il/5Zo/abjj/zTI7wVWrvYJv/ZYsX1OwmIyefro7G+tECwCgaDLcuLEKlS1LiPswoULmTJlCrNnz2bmzJmYzWZiY70OrnKtc6ZZa0YrSUy7dc4pn9/pdFJcExiKW1NtY/79C/muxIpHVTkvxhKwXaOR8XjqLv12hw3w5kHZs2cPhw8f5vDhw10m0y3gv5PJTSRxC1PCKIuQ6kKRfYfVJn9Tpc6+FQqaI1SMgWJJSCAQdFlstlxiY8/1Pz85PNiXl2XZsmWoqkp+fj779x9Ao9HyxcvLgzKGSSOG8tGRA3UNqkpvs4FpsZZG9zeYteTuLUWrq/VpUbQcPnyYmpoaUlJSiIyMbPS4rkBTgkVWvXc8xR0oTHyWpvbIFZ9V5kxaWhM0jxAsAoGgy5KYOIfS0h+pqPiFhITZaDRmANzuKgoKVqBSN6NPS0tj+fLl3pukDKWlpUEZw4EDB1reqR6xyeHEJof7n/eqDXHuyviWZzRNZaWtXbZ5afuLPJfxSoPjEBaWLkFnJ1EVgkUgEHRZ9u1fSKRlBMnJ11FRsR1VdeHx2Bg9+mZuu20mGlmLw2ZDVRX27N5NWKSBggIFj8cRtNT3mXl5Le90hnHFW1fQJ6sPOkWHJEkYPd58Nk1ZWPS1t5oy9aQkfb7U/+3xYel0jwrB6UYIFoFA0GUZNvQlwLssEBMz0d8uy0YMhkSOHc/low/f5fjx4xiNRioq626Yntpqv21hYJ+eZOefwGari0SqKmlvaHTXxVhuJNwdHtCmoJDWPa3R/e/ueycPZT8WuL+iULbrOAkko4pVnS5BZ4tEIVgEAkGXpTn/BYOhG26Xhy3bdiFJEooKTmf7HVm1Wi0HMo8JnwlgaNxQHMUOqqKruHbWtSiqQnJsMskxya3uY+Pa7xiY5d3fpW+7eBRRQqePUPnKiyghgUBwxpCamsqyZcsAeOSRRwKqDdtqavCcQuSN2+3GbDZjMOgabGutiKk/Ph8ZGRksXry43ePqDIxa7xKQ2WRmdL/RjE0b2yaxAlBZVWftSp8/JajjE5yZCMEiEAjOOOQg1pcx1qs3VF1d3WAp6eTCir5zNyZO8vLy+Prrr4M2tk6nlSsEvt0CrCG1EUNZCUXEJ7Q/J46weJ0+OtvpVggWgUBwxhEfH98uH5XGsNvtAc9PXlbyL03U3jgjIiKatZisXbu2gZB56aWXupyV5ZSpDeBS5FO7C6qdfRc9CwgVUSgEi0AgCCpHTlTxzZ4CnG6Fe97fzrS/r+GX7LLTOoZp06ZRVdUwRX5HIQM6rXepKDys8fwrAC6Xq0FCuAMHDpzWsTZFW278QbmB1VpY2itYfGPobEfQs4nOfqeFYBEIBEFjxfbjXPjMD9yx/Bf6//krPt12nKPF1Vz54nqm/b81/Gb5L/xw8ASeDkpNL8syuTYHkdOvx2AwtnxAkFCASRkTAG+6/sGDBpKdnc0f77vPW5BRkjDVLi253W7+/OCDaLVawsLCsdvtOJ3OZnoPXeR8mRUbV7S8oy/dSr0mKUgWFkHHExr2FSFYBAJBEHntx0zcTYiRoyeq+XnPQY7953Y+f+4ucATPqvDG8WL+djQfe0Qk1qJCrh/Vl6iUfkHrvyW0Gi1rf1mHJEmk9uztz+Dq9nj8tYzsDod//+qaGjweDzU11YDX8rJmzRqg851wW2M9sdSzIq1fu74VvQZ+JwqK84jd57VIqZp2Wlhqb6NiSejsQYQ1CwSCoKCqKj1jzOw8VoFeI3PzpFTO7R9Prxgzq3dmEbnhCa5wfObduRw872ahufl/QTn3zclxFDlcnLhoBv9+403OuehiBgweTP7+nUHpvyXcnrplnh27t1JhrWhm767PddOu4+95f8eT40HytH3+vfudtQx09gBANbZv/u4XLJ2+UHH20Nni8JQsLEuXLkWSJBYsWOBvU1WVxYsX0717d0wmE1OnTmXPnj0t9vXxxx+Tnp6OwWAgPT2dTz/99FSGJhAITiOqqnL78l/4Ymc+ANeP68WimYOY1C+OntEmblkzoU6s1KLJ+gFyNwdtDN0MOv764INMn3oud141l93r1wat77ZgrbR2ynlPJya9iXEjxwEgqZLfitQSPpGht3uzDNfIdgaeP6ZdY/D7sAgLS4cTIj637Rcsmzdv5pVXXmHYsGEB7U8++SRPP/00zz//PJs3byYxMZHp06dTWVnZZF8bNmzgmmuu4aabbmLHjh3cdNNNXH311WzatKm9wxMIBKeR7w8UsWpvIQARBi3zJ6b6t21/7hr/4+/kCeRc/Q2EJ3obXrsA/j0Tqk4EZRy+4odV1go+3bM/KH22lbPlBuoTDAaXgUXLFrVatNSnaIqHHj17t+/8wsJy1tEuwVJVVcUNN9zAq6++SnR0tL9dVVWWLVvGgw8+yBVXXMGQIUN48803qamp4Z133mmyv2XLljF9+nQWLlzIwIEDWbhwIeeff36D0D+BQBB6rD9SzK1vbAHgurE92fHXGfSOCwNAcbvIKPsGgP30ZtpfvqZX+nj4/RZImeTtIPsn+O6RoI/rnOgIIuPigt5vR+NyuTp7CK1ieOpwXLJ3rEarkapmfJIUGhczpyTuamf9QrCcPjr7nW6XD8udd97JrFmzuOCCC3j00Uf97ZmZmRQUFDBjxgx/m8Fg4Nxzz2X9+vXccccdjfa3YcMG7rnnnoC2Cy+8UAgWgaAL8PkvWfxTt4w06Ti5RRdyZOssIhNSiUvsyba3FjIKcKsy4fPfqzvIEAE3fwEf/wp2fwwHOiaZ2o9frGbouIwO6TvYTJ06FavVSmZm5mk75xc789mU6a2FdOjQYcpcvdhwUGH1ss/9NyfV/08dPpHgNo+hrKwcgLX/+gCNpvaWcpIQqaypxOaeywFPNL9/4gdqysMwYGPXz0eJzHuZoWnH0DQTLdSYKMm15tYboKAjCZXyB20WLO+99x5bt25l8+aGa88FBQUAJCQkBLQnJCSQnZ3dZJ8FBQWNHuPrrzEcDgeOel73VuuZv24sEIQij0WtQNL8DED/gtfh89f920bV/r9+wANM6TMw8EBJggEzvYKlughqSsEcE9Sxpard0Ol0XcJq8cXH77Jj/Wo00um5AzvcHha8vw2Xx3c+PeC9Dh9o+tJbi+8GJgPx3ofHm9u/GwD5wP/wuQe4wJZK7iE4Yv8abfjhtr2AWiyGpvPeCIJMJ4vDNgmW3Nxc7r77blauXBmQrvpkTg6LU1W1xVC5th6zdOlSHn744VaMWiAQBB1VBXsFvH8jUtY6bxMym00T6W3bQ6RqRS95M816VIlzrrm/8X76Tqt7XJYZdMGijTYSFxdHfn5+UPvtCHYdyub/7ltEZlbTk7tgoqr4xcqtk3pj1EJuTg5utxu9Xu/fTz7pMlz/uiwBVqeVGm0NunBtQLvKSfk7qj30k1Mxy2ZKaorZWraNLFcaNXYDl/a5kv496iagjV3768/yfY8TwhIYlTCqwb6C4BIqTrdtEiy//PILRUVFjBpV9wXxeDz88MMPPP/88xw4cADwWkySkupqQxQVFTWwoNQnMTGxgTWlpWMWLlzIvffe639utVrp2bNnW15OmxDrpAJBLRv+Cd8satAs3bOLsZHeUNW841v537rHGWqeQuqQC+iuacRdzuOC/V94H8taiE0L6jBt+0vRJYZx7bXX8vzzz4eklSVjyAAOHDyMOSyC/7vhEuZP6sH8L16HtOkdfm5NPSVy9/lpRJp1QHqHn7eOGVz2z5/YkVvO9JTpXJDe9PVeIIA2Cpbzzz+fXbt2BbTdcsstDBw4kAceeIA+ffqQmJjIqlWrGDFiBABOp5O1a9fyxBNPNNnvhAkTWLVqVYAfy8qVK5k4cWKTxxgMBgwGQ1uGf0qEyhqeQNDp1BcrhkiYfA9MvBtqi/6V5m9jwdfz2acFg20/U77/N/ftGEP3xAyIToGkDK/o2fIauGvr9Ay7FozBNe1LOhk8CosXL+b48eN88MEHyLKMpNGCojB75kxW/O+/QT1nWzmak48HDYpGB7F9oM95p206q6l3Hnc7InyCgr8OU+ecXtA2Onvi3ibBEhERwZAhQwLawsLCiI2N9bcvWLCAxx9/nLS0NNLS0nj88ccxm81cf/31/mPmzZtHcnIyS5cuBeDuu+9mypQpPPHEE1x22WWsWLGC1atX8+OPP57q6xMIBMHm5i9R35jJXr2ekp5DKa/JwfPd/WRZszlcdYwflUoUrfcO5JAlVsluiou+56ndH5FwckFCWQuDLoHZzwR9mI6jFZBqwZIWzfvvv89nn33GpEmTWL16NWUfHMRmUTtdsABER0djd9UmngtilemWkGUJWQJFhYdW7ObpqzMw6jSn7fxQr4qzECwhTah8PEHPdHv//fdjs9n43e9+R1lZGePGjWPlypVERET498nJyQko/z5x4kTee+89/vznP/PQQw/Rt29f3n//fcaNGxfs4QkEZxzVHg8Hqu3ISETpNKSaOs7yWOOq4cm8VXzZOwUbKnhyID8ncCdJYpCq45aBN3DcmsOz+d9hOqrnp18SmDiglMR4OxgscMkySJ8DcsfcJFW3gjO3EkduJfoEM0adgTVr1vCbS27m1qvmsfQ/z3bIeduCx+Phlltu4ZllnTOWuHADRZUOvtxVwNxRxUwbeHqXZXzBRMKCLWgNpyxYfPUvfEiSxOLFi5uthXHyMQBz585l7ty5pzocgeCs4uXcIv56OC+g7bJuUVyR4M2P5LsNvHrsBJFaDf3DjAwNNzEhKpwoXdt//veuuZef8n7yP09zgyJJhGkM9DfEkmSK49zB19O/z0VItZOSIbu+InKp19+s7FgMCavfQ4rtBaboRs8RLKIu9iYkq1qfR82OE0RFRWFz2vnPtx/w9Y7v+dPl/8c3upU4XJ1XeNDhcvPvtz9AlSSySqpZe/AE3SIMDEo6PZEv//nVWC5a5nWadrpPv7lfbawqoiBk6eyciKKWkEDQhTlZrACsKCpnRVF54wec8Na4idFp+GxEGv3Dmo72q3ZVY9Ka+CrzK744+gUVjgp2Fntr8zw66VEyumWQYkkJOGbflpVUXXk3+x1/8LdFntSvo8qAsUfHihXwRhoW/e1v6FIzkCSIM5oo0+r409wbeemrzyg4sR9nJ4oVAI/LyYhhgzl8xERqbBjn9o9n7cETDEpq+dhgMDDRwsheUWzNKe+UZRlV6JWuQYh8QEKwCARdmJ0TBzNsvbdW14N9klhbWklNIw6UigqlLjcTosL5qbySY3YXN+w8ytqxAzE3EsGzuWAzt35za6PnHJs4lsv6Xdbotr2PLSLd0bDdqQV9rZtG5pzLSf3gfUwnlfUINjUbNmBdtYq07xYCcPg311Jlt5Efqcet0/C3T94Oidg/OS6V/776FkWVDtYePEHPaNNpPb/fj+S0nrX23D7BIpxYugTCwiIQCNpNN4OOsZFh/FxRTS+Tno9G9GvxmBKnm2mb95Nrd/JUZj5/6du9wQ3D6qxLxBimC+Om9JvoHtYdo9bI1J5TG+23OO8IfQ9VB7TtvnQwvS6+krSMqbhff4eSV/8FQNbV1zBw394OvVGFTZxIwv33ozgcyAYDkZGR2Gw2nn/+eQB0Ol2Hnbv1SAxMjGBQkuW0WVVOpjNFQ2eKJUHrCRUfIyFYBIIujKKq7K2yARCmaZ3zaqxey+J+yfx2bzYv5p5AliQe6ts9YJ/0mLp8HF9c/gWxptjmx6EobLrzRvq4Ia+7gamrtiDLGgbVvwn+4Q+oikLpa95MuKrLhVQvQVlHEDF9OuUff8x3pZXYrZVE6vU4TSYqKyvRarWdnptFVRX+8fRTRBh1zfr9degYav/vzFuSMLAIWsPpi6ETCARBR1Gh2uNdAurThuigyxOimd/dK0L+mVPE5opAy0icOQ6L3uv4ua1oW4v9Hfj5G/rsK8ctQ/LjS9FotI3O2OPvvtv/WHU0snYUZCSNhrCJE5kcZkAyGkkfMQKr1Yqqqnjc7g4/f2twuVysWbOGjIyM0ypatuaU8eGWXEqrvZ9D5/iwhMKinKC1dPanJQSLQNCF0coS4yK9lZE/LCht07FL+/dglMUMwBXbDvNMVgHflVh5L78Eq1ticOxgAD4+9HGLfRVs3wDA8T4RDBx/cZP72eslnlRPk2DQ9+hBt5tuRDIY2LF7t7/d2YnWlZPFXFZW1mk9//FyG1e+uJ4/frST3FKvhU6v7bzbQagsOQgaJ1QsYGJJqBWISYAglLk4PpKNFdX8t6ic+3snttoXQZYkPhjel7v25/DFiQqeyKwrj5Goy8ZdsBUJ0MvNL9soioL989pqy2mpze6bfcON/sfa6I6PFKpPSmICP+ecnjo9LdLJF5Uiqx1VBYNWZlK/OLpHGRmTGtw6Tm0hVG6IgubpbIuYsLAIBF2cKxKiMckSR2wONp60tNMSYVoNrw5O5R+DejE+Moyw2oihApdMRdxdGLXh3DH8jmb7WLf8CVIPV+LQwrBfN1HkEHAVFrZpbMFm2rRpLe90uujkO7RSe+NJjDTy+s1jeHTO0NOe5RY6XbcJWkmo6EkhWASCLk68Xsel3bzWik8Ly9p8vCxJXJUYw2cj0zgyZRj/7KsDxYHLNAxX/O30i2w88shTUcG2JX/E8sxbABjccGD1RyiNhVUrCsWvvOp/HvPOOxw7doycnJwG+3YUCxcuPG3naokGM1WXjf379jaaVLMjcNdWadaEiGkjNEYhCHXEkpBAcAZwVWI07xeU8m5+KX/snUi8vv0hu1f0TOdQ1RqWFego0I3gjztW8uyo2Q3223/tVRgzcwPaTG99z/LttxKfNoA+Y8cy8PzzOfD113y8bh0eSSL2vKm4dDrK/rvCf8yYMWO46KKLUBSlQ0ONh3Vw3pdTQdEYcLrcbNn8c4uZwoOBp1Yw1a/Y3Bl0djE9Qdvo7E9LCJZWEiITEYGgUSZFhZOo11HgdHHb7ixWjExrd1+SJPGn9PP4/sQ77FDSWVXmaXQ/7e03oixc6n+uSBJrp56LzWwm0+Hg53XrYJ037Tu1QqQooWGtms2bN7N582b0ej3z5s2jR48e7R57V+XYsWOn1T/AZwTrbMHiJ0SGIWicUEnsJ5aEBIIzAEmSGBfljRY6Zg9OuvnJMd6w51K5B+Uue4PtAy6fR8FvLiW/u5GsQdFkL1uIzeyNOtKcVJXZbHcwt39/xoaHM2XKFBYsWMDixYtJTk727+N0OvnXv/7Fpk2bOuzmLZ/GashtQa/Xo63No/PSSy91uIXFXatYOluwiOKHgrYgLCwCwRnCXSkJrCgq57jDxcriCuL1OlJMemLaUeQQ4K6BU3h57Xpcmlie3LeBx4ed12Cf8xY8AQueACC3OJeNGw4hI3PptZfCvmzsNTU4a2oYf9NN6MLCGHLS8TfccAOffvophw4d8rd99dVXlJSUMHPmzHaNuzFSU1OxWq0t79gJyLKMx+PB04jvT0ehhMySkKAr0dlO0kKwCARnCOlhRiZHh7OurIp5uzIBGBRmZPWYAe1yrrToTAwz1fCLM5aPTjh4vIX9e8b1xG6yY7aZ+XbvOu696t4Wz2E2m5kxYyzhEe/i8ZRwLDed0tKelJa2LadMa5AkiYiICCoqKoLe96ngKxngdrv9QqKj8TvdhsiSUIisOAiaIFQ+HiFYBIIzBEmSeGNob+ZuO8K2yhoA9lXbeTe/lBu7N59a/2hlKX/a/Apuj52R8UMYYJrE3hPVHMiMQCNVUxneypwpBsAGitSytUBRFPbvX0FW1uOEh3sFisHgYWqPuxky5GRbzKkTHh5OeXk5RqMRu73hEldnUVFR4Y+sstsdWCwdc54fjv3AN1nfoKoqu46XYexeyT63yrTlr6OqSq0DrIqqqqgoWDwlDLKXcmNlOHK9W1Z9TaXW+/ek/xpFOunBX2xusrVxyMqoYLxEQYfTuSYWIVgEgjOIMI2GT0f0Y11ZJStLrCzPK+HPh45hkCXmJkQ36jy3vugIv/vu93gc3oifQ3kfU5NzK57q/gD44naKLiinW3hUo+etqCpjxSc3ck7ffE4U9Ua1x/LVV3NAsjFk8MNERPRCUVxERiajqqAoDr797hb0+l8wGOuNP8zRYdE8aWlpfP/998RERuNwODo9CZaP+mHgqqp2mJhasnEJBdV1yQF1kd7/TzShLcs0kB0Gt5QfId3ZQVmBJUALx2r2AYkdcw7BKRMqFjAhWASCMwyjRmZ6XCTnxkRwuMbOhvJqfr8vh4PVdh6sV+Tw82O7eGLz3ymzbkNCRZXDkBRv4jlj0idU590LDgPULh+c+/R/2XT/XCxGc4NzfrfrTyT32A9AWO/tAdsOHrqh0XHq9aCqEh73OLS6jbVtzVuC2ossy5x//vl89913lFaUoaoqEp09X2yI2WymoqKiQ/Kx2N1eIXTL4FsoqzTw1a5CLEY9Q5KjkCUJCRlJkvyPvy58DoADPa+kImwoEvVuXJLXUbZ+m4TkfSw1XEJQ/f94LTS+cObR2xYB0MMSCpWzBaGOECytINQuagJBa9DLMu8P78szWYU8k13IPw7ns2pDLneO6cX3J95j3RFv1WQJMIal88LUx/l231GWH3wIWVfOjJE7eGX2Yu767AP+u0mHrSaWxd98zdOXXRFwnuLKHAxV30FtolS7fRhw3CsKJDdGY+POrooik9DtEbp3T2DHTq9gGTJ4WYe8F/Hx8fx89Gd0Oh1jhoxk6+6t2JzBiaYKJk6ns8MimRTVa0qZkzaHPpF9WNLQhzqAHa8/S75GIm3UBQxJv6pDxkTum1B8oGP6FgSdzjZKCsEiEJzB6GWZ+3sn8mVxBUf2FpCVW80fdxcTPvB1/8z4iQveY2ayt9DhmMl9Kasq4MuiJ9l4YiXVzgd4bs7VVNiXk705jrIfZN7TfkVldRXVOSrOApl4UxG9zvPeDEdOWE+0KTDXittdiSzrsdtr2Lz5aUzmRBTFSWzMINLSLqKw8Av/vhERQzvkfZg2bRr/ev1fKLLKlj3bUFQVrUaL2xMaFZt9uN1uNJqOSZHvs2q0NoTYd2+SpNAMBRecPkIl7FwIFoHgDEeSJJYP7c2UT47422y5t9Ct7xG+u+ZZTJrAy8DCc+fy5buvomrLeHzdmzx2/m+YkzycvDXFgIGS/wEY0OH1b9HF7/UfG6FpWEBPq40AwGw2cO65SxpsLyj0Zr1NTr6hwxJU3f/An3h62bO47S5UrRaP2x0yybBORpIkpk6dGvR+fT47chMCZO/+z3h8wyNUq248QIHGt9YTmu+T4PTT2asNQjoLBGcB7qpAp0lP9QCsR8fgcjV0powym5gQOxeA0jVlLLn3W/LeLvZvt+urAvZPGvOm/3HmVws5/L8H2PHOldQcb9nUX1V1kOLi7wHokdy4r0swiLRYiImNIzwyij/85RH0YWHozaYOO9+p0FHOwC1ZWL7a/SY7ZBeHNSqZGu++OlUlMS74EVuCLkaIaFZhYREIzgJeXOO1rvSK15JbVozqjqK6Kp5hS/7H5HQ3N43JYEb/dP/+j5xzNa8uMRHj6Otvq9DDueeAmlXMzqMmVDREyEWoO8cgDdsMQE7Ep96dw6D6m2uZMH8LUjNLHOXlPwMKkZYRhIcPCP4Lr0WWJQxaGafByMpf9hAdGUlMTAz7du/usHO2F4+n8VIIp4rPh6Uxy9KxYxt5q+oQSBIztbHMHTwPWdLQM3EUsXH9O2Q8AkFbEYJFIDjDWXvwBB/+cgyAZ+aOwWCo4dLn16O4w8ATxrpd8OPugyy/6DD2nT/h+HED3feUMqTnJPJSvIKl+wgPvbLy2P5dTyAVgL6G9UyPegZNuZusdWlkZpSjRNRZB2ypVn7471ASpQvoM+MRtCZLQ3+I2ud6Q7cOfQ98mW779OnD8U3fYnO5OX48r0PPeSp0ZNXmxiwsi1bfibtWyKSGJTMm49YOO38gnb3IIGgLwulWIBB0GDOeWcvBQu8SzvwJKYxKiQFiOPro1Ty9Zg2r9x9jb1Y0qqrjpyc+YkDNQawmPfvTU0A6jt6dj6RJJG+bBuiJhIfehp9JN6+ml34rkgQOm4VeCz8nNSqRmmP7sZUcIXf3K5Qk7cYd6eAYX3Bs4xdoKwwM6vs43YbN8Y9PkrzWF1XtGKtCfTweD9OmTSM7O5sPP/wwZH1YOgqfhaUxH5YyxQkaSPXAnLEtZygOGv474Nn1WXQ1QuWnInxYWkmIfF4CQZvwiRWAW8/pHbDt3qlT+eKOG5iR4w0pXp/SnyMJ0ZywhPmvUM7Kd3GUP4OqOuht2Mj1cXdxcfSTpBi2YlMHUtN/AfpHjyBHeZN+mXsMJHb4LIZd8yH9Km/GeMDgP5870sHBfX8JGINUGwtdUfELJSXrsNmOB/9NqCUqKoqCggLuXPQoOp0Okyk0fVhkWe5Qp9vGLCw+2fDwqD+S1P10Zp31VT8UV1hBywjBIhCcwTx33Qj/41V7CwMcOlVFYdVXn/Jtj9EAGBRHk/0Mdj3LxVFPEKWtW0Yx/OZtzNc/jKTTN9hf1upJuewhJv12L2O6/Yd+jl8D4IyoxlVZ58Ary95jXa4ytu+4mY2bZlBTk9nOV9s8aWlpfPbFV+zZsRVkDdXV1bVjODsugwpN+7D4kt3KcseEVDeJsLB0KdROXsI7O36pAsFZyqXDu3PtmJ4APPrFPkYuWcXCT3ay+3gF33z1Gbf/YMAje1eGLe7KJvtxXXOYI70DM9w6l13cqjGEp4+nssob+qwaoWT/V/5t3bpdSI8e8/zPFcWO3Z7fuhfXBnyZbgdljOOB39+O2+nw5ztRTmOV5NbQYQLKZ8xoxsJy+i0dwsLSFQiVT0cIFoHgDGd8n7p092U1Lt79OZe5L63n090l/vaBtnIGOBT0ETdgiLwDnflC7Am9sCX3Yci8g2h0Ktk9TRzsE+Y/xp3WchhyedZPbPlgGoWxPwFgzLcQN/gy/3ZZNjCg/19JTr7R3xYREfww2vj4eMrKynj4mSfJyTtOXLc4VFUlPjIy6Oc6FXTajnMr9FlYGvNh8QkWWRIWFkHTCKdbgUDQoVw6vDs7j1VQUu2g0Gpn49FS7C6FdeVeIfPyNInJGTPY9b5KSVY+sruG3WGpuCK9kTvbdl3CmLGfgSSR28NEbg+v78c5I37T7HmPfPEgWab3oDYAyFLRl0GX/gO7WghVBdTV+lVR1bp8MEVFX5KcfG1Q34PzzjuP119/kXOnDuLNPT9SWWFFK0vccMvNfPzxJ+Tm5gb1fO1FUdWgWFhUVcWjemrfWxUV1e90e8J2ApfiQlEVFFXBo3gokRRAxla4h+K4nSiKB1BRFQ+K6vE6RSsqKh5URal97kap7bu9pJZ5l/8cucdQbdF+3RKwbFX72FNejru0FI3FgjY+PrCwEYEPGzueltqQkHRadAmBmZoFjS8jdgZCsLSCUKnqKhC0B1mW+Msl3hwrdpeH8//fWo6X26hRvQ6x6/ZkMWP6xYz7/Y2Qtw31XzMwWa/le7yCxm6PYMP6qxk7/iM0ct3yifXoT8SPurLJ8xaWfQ31/FqtkUfYtHlmi+MtLvk+6IJl0aJF7N+/keuvW0BkZCTxljBsHonIyChycnKIi4mjpKyk5Y46GI/HQ2x0w2zBbUFVVW795la2FG5pdPs1n1/TsLFWJIVtfJG4H549pfO3h7w/3o+9tKEvVGcQ+5s76LZgQWcPI6SodnhLWHy+M49LhndvYe+OQwgWgeAswqjT8Mz5Zq79uAaldjr6VmEK1x48zJABabDxRSTFybl9tqAx3cCmr79G0epxxiRQmBVJ9z5l/r525d+P5/evE3/5PIafdzUbnnsI6e3PcITpGP7Bf+md8nsO5i7BYwHZaETSGwCpdrZ20sy2ts1s7kP/tMBIomBgsVh49dVFxMfPAOCBP/6B11/4J+dNncLu3bupsdeg1+rol5rOgex9eFynvzCiRpaRNRp+87vfsnjx4nb3U+4ob1KsNEdvp4s+LhcuvLYvVZK8/wMKEqpU2463Xand3n681p8Tig6NNhFNnFy35nDy/4CnrO67p6ldyvNvrT+pbKYP3+OAcfva3G5wubDv3nMKr+nMxKj1LhUO6d65S6htEiwvvvgiL774IllZWQAMHjyYv/zlL1x8sdf5rrCwkAceeICVK1dSXl7OlClT+Mc//kFaWlqTfb7xxhvccsstDdptNhtGo7EtwxMIBC1RlsXYLy7kds21vOS51N8cG2GG8lzY9SEAroueJuf1jwDoPWQIh3ZvoWZvONQTLKoZLKaDSL9fzJrEJ0k8XuPdYPWw592XmfSbv1D+6ycAiJh+Pj3+8dxpepGNYzT24MSJlYwaNY8bzhvF5KmTufSyy4mMjMTpdGLQaJk150KSNibz7Y9fAtCrexI5ecF3Am4MjUZDVHT0KZvf7W47ADpZx/dXf+/1WVG9S292jx29rEcra5FlGQ0a72NJPu1m/08+WcpfK99haFk47/zw02k9d2NUrFhB3gN/6uxhhCQ6rfe70SvW3MKeHUubBEuPHj3429/+Rr9+/QB48803ueyyy9i2bRvp6enMmTMHnU7HihUrsFgsPP3001xwwQXs3buXsLCwJvu1WCwcOBBYd0SIFYGgA9j7XwB+rf3CL1juSismqXsyHFqFoij8VNyXnxc+5j+kz6ix7N+3marj4WTXxNHdVIyu9t7miQS9BxKP16BIINdOXWNf+Jj9L3zs78OYPuj0vL5miIhIJyIiHVk2EmHqxidf/Nu/zaTXM2zkCJ586glSU1ORJAlVVendZyAuJ5RWluJwNB32HQxUVeWOO24/JesKgM1jA8CkNRFpCJwRW7CcUt/BpK3VowWdh+8z6mzviDYJlksuuSTg+WOPPcaLL77Ixo0b0el0bNy4kd27dzN4sLdU/QsvvEC3bt149913ue2225rsV5IkEhMT2zF8gUDQJiq8zqWxUiW3WzaS6YziV7Ov8m4rPUqZ08zPxXVr1OdcOw/94B6YHF6T8LXnrsIYHs7xst1s3PUow2+7m8oRhyk9soee4y8g97FH6LE/0BdE16sXkVc07etyOnhzfRYT+8aSlhABqopSWuPfpqoqYSYzu3btYt26dbhcLr/fmkaW0ei0xMbGUlhYiKrUObEGG1VVg3Lz9llYjJrQnvT538MQcRH0+yqGiINpKOF7Szo7D0u7fVg8Hg8ffvgh1dXVTJgwwT/7qG8Z0Wg06PV6fvzxx2YFS1VVFSkpKXg8HjIyMliyZAkjRoxocn8Ah8MRMOOxWq3tfSkCwdlDTan3f1nHoj897He2BEBxE2uou5GPv/Jaxl1+NSt//gQAlx7MEd4Zes+YYfQ89wPvjjMn+Y+JeKobq++/Ga3Dya7eEqsn/ZXrJ07h3oSOrRXUHFUON5V2F5Ik8eWufBQktDHReKqq0ISHU5hTQJgpgoRYC7Nnz6a6uhqtVovH40FxetBoZVxOJx6PB7PRxD2/vounXn6G4QOH4bQ52XFop/9c/QeN4OC+be0ap0dRkIIQIWRzey0sRm1oCxb/vU/ogy5Dl7KwAOzatYsJEyZgt9sJDw/n008/JT09HZfLRUpKCgsXLuTll18mLCyMp59+moKCAvLzm14DHjhwIG+88QZDhw7FarXy7LPPMmnSJHbs2NGs78vSpUt5+OGH2zp8geDsxV4Bu71+KSiuQLEC0P8i+GYR4+Jy2VTck13ffsPO1V9TU1Hu3e5R+NWnT9I9IoGDRcdIjrDzx8nXkxRVt9yz0+jm73M8UJtyvyQ+lqezChgYZuTcmAjCmqnc3BHUON28vzmXG8alEB2mp298GB4VsqO68+VnP2AKM5NdXIVLp+eqq65i8eLFpKamApCdnY3Lakd2QVFREQB2p4Pq/HIURWHvkX0Nzpefc6hd49RoNGhkmZdeegmgTctCi9Yt4ofjP+D0OHF6nHhq6zKFumDx65UQsbAImsZvYenkz6rNcn7AgAFs376djRs38tvf/pb58+ezd+9edDodH3/8MQcPHiQmJgaz2cyaNWu4+OKL/RklG2P8+PHceOONDB8+nMmTJ/PBBx/Qv39//vGPfzQ7joULF1JRUeH/C5U8CgJByNLS1Sa2L0Sn0jfcu6RTXV5WJ1YAnUfmZ+tyPjv+d/a63mNV6WfMXHENL2/4PQArsjdx/3d1DvR/Pvc1zuvWG7cKt+7OIu2HXcz85SArispwnqbssmU1LpIijXy7vwiPoiJJEj2SEohQqrjkxplMvGgikyZmUFxUV3JAlmXOGz0Rs9HET3s3klmQHZDa4KudazBo9aSkpFBTUxNwvsrqKk6mNXlVFEVBp9W1+fXZ3Db+d/R/VDgqsLltfrECcE7yOW3u77RSmxcmZAwswuLTJHKtYulsbdlmC4ter/c73Y4ePZrNmzfz7LPP8vLLLzNq1Ci2b99ORUUFTqeT+Ph4xo0bx+jRo1vdvyzLjBkzhkOHmp+pGAwGDAZDs/sIBIJ6mKLgxk/grSsgvInkWGHxJBqziI2NoKSkEo1Oh8flTeqWHWlCcUWiuKJQ3Ra0hkLchiL+efB7ZPNLvHTwW383d094jmtSxzLD5ebvmQV8XVzBcYeLrdYa7tiTTW+TnqcG9OSc6IgOfcnJUSaSo0zUON08veoACy7oz7Rp03jjjTe45JJLiI6O5s9//jMajczuw6UczanApNGjNZvILyxg5kWXsn3rZqodNWi1WiRJYuCggejcMlfMnctjjz2Gx9P2StOyrKktCVAbUquqjBySgdVZ3e7X+vGlHxOpj8SgMaDX6DHrOjeio7UIp9vQx/cJKZ1sYjnlPCyqqjbwno+sjZE/dOgQW7ZsYcmSJW3qb/v27QwdOvRUhxZUhB+W4Myg9oJTVQgHv4H+F9Zt2vc/OLYZSZa59t67cEb2xRLv9T15ccsyPtk8HO3hOovCU7NKWVH8GjusJTy3/Z/+9kVTXuO63mMBiNZpeax/Dx7r34M8u5O38kt483gJmTYnc7cf4a5e3VjUt+MTUZn1Wm47pw9bs8tYuHAhR48eZfbs2URGRrJkyRKysrIY3DeaYyeq6d57IJ+v+pJ5O27mycV/5ZE/PczK7T9w/vnn8/XXXwPgyLYyZsbEVomVxmoVKYoHSZJPOSllhaMC8KbbT7WkoteERvK11tDZs/UGCKfbJpHqvG47lTYJlkWLFnHxxRfTs2dPKisree+991izZo3/R/zhhx8SHx9Pr1692LVrF3fffTdz5sxhxowZ/j7mzZtHcnIyS5cuBeDhhx9m/PjxpKWlYbVaee6559i+fTv//Oc/Gx2DQCA4BfpMg6FXw64P4IenoO/5oNGCoxK+qs1BMWkBxn4TqO8B8aM0AfdAA54EM6bsMlKcR4lL7scFtkoKaxRKFR0ORaF/8lV+sXIy3Y16/pCaSK7dyYcF3nwu5e62WyfaS3SYHo+iUqXoeP/99wO2zZ8/3//4X6+9wLwbb/ILmnuuuo1vd/4YIC4MKRZU16kta6m1SyLhZhM2uwNFUXC5XC0cFcjq7NUADIkb0qXEihdfWLMg1PF9Rl0qSqiwsJCbbrqJ/Px8IiMjGTZsGF9//TXTp08HID8/n3vvvZfCwkKSkpKYN28eDz30UEAfOTk5AWu65eXl3H777RQUFBAZGcmIESP44YcfGDu28YteZxByMwGBoL3IMpx7v1ewHNsM2/4Do2+FbxaB9RhEpcCUPzY4bJvNDHhQow3URCeyj0Rqsq6np9bBn5IgP/5urhp0MwZt8zfNhw4d94uV65JiWJKW3BGvskkm9I3lq90F/JJdRkbPKHrGNFw2ibBY+POf/8r06VP8bcs++Bdje3mdi3fllpFTWoNNe2q32jC9Fsmk5eqbZrF+9W76J6by3ncr2tTHl5neBHcze7dc8kAgaC+h4nTbJsHy2muvNbv9rrvu4q677mp2nzVr1gQ8f+aZZ3jmmWfaMgyBQHAqWOqJBGcNFO6Frf/xPr/0OdAH3sRVVaXM5bWE3NrNzetF3svGb/g3c/iYOXzMlYPmtShWbB6FN44XA/DMwJ5clxTb7P4dgSRJzByahEdRWb2vkF+yyxiQGMGgJG+4tt3lYV1mBWnhGsoLC4iIjUOSvVdr2eB93YcKKrl0ZA90uraHIEuyhKqohBl1zJg5gvU/ZXHVrF/x9qtzqHHVNBugcDJHyo+wq3gXsiRzYeqFLR8QaoTaTFAVieyaQuqqTrcCgaCLozOBOQ5qimHTS3DgK2978ijoM7XB7vkOFypes/BfBo6k0LaWLyqjcUkGPlcvYyrfY2pFCO0HBaX4FlEMQcg3cipoZIkLB3uTVf50uJjPd+aRFGmiuMrB7GHd0cjJ7Fn7LYrHg2xVUZxuIvt05+fDxfSJMaPVyMi0fUlIVbyXfJvTw69uWURe3kJ/aZNefXsRHR7d6r5WZq0EYGL3icSZ4to8ls6ms5cXBG2nS1lYBALBGYAkwRUvw1tXejPf1ma/5fzGiw6uLasEYHiEmTyHkx9tsVB7sx4v/YwmqXmrKkBmjYMHDh7zP38/v5QrElp/c+5IJvWLo6LGRY3LzaiUujH1GzMendGIdeMxEpOS2Hswi7FuD2MHJmC1WsnMzPSn8G8rsbGxXH/DPCIjI+nZsyfV1eWkDU7j9W9eb3UfDo832KF3ZO82nz80CLU4YiGgmkOWOl9kdu40RyAQdA79LoDBV9Q975beqHVlQ3kV9+z3Cpq+JgOTN+2nwu0VK7PiInln6gLmDLypxdP5RE/959+WhE526kizjqRIU0CbwRyGLGuwjExm0uDxfPjReyhFB9i9ezfz589Ho9Gg0+naVTSwZ2IMRw/uJicnh5iYGC674hx+9YdftamPzr55nLGIKKFGkSQJRVhYBAJBp2CpF07cfWSjuzxYzyqS63Dii+l5on8P5ie3fhliTrcoipwu8h0uNpZXkWlzcuvuTD7N6MfIyKYLo4YCil7DBY8tZE3FMS655BJ/KHRmZiZZWVkk9u5B3pEcPB53q03m4dEJlOQeJHf3emxV5bhdMe0en/C5EJwOJOj0NSEhWDoBd3Extp27kHQ6Bl99Fb+bexV3Xn21f/vEW29h9jmTWXTrrY0e78xTkM2xGNKS/A6BnYEcrkPfPbzTzi84RaY9BDG9oboYRjRuJXm4XzJX7TgCwM8VdUnN2iJWAKJ0Wu7vnQSAQ1G4eVcm35dWMn93JvelJlLu8mD1eJgaHcH4qHB0nfi9Phm7onAYLY/9+03OjY7gp/IqdJLEM7Mv547zpjCiT3/+9MqLDBw5iZEjh7H/0NFmepMIDw/jvPPOo//o8wHQGh7B5dLw7dGtTEqe1MyxgciS10CuqKcna3Cw6Wx/iAaIPCzNIkmdv2gmBEsnYN+7l4hp5wEgGQwY+vYhfHJdGm05LAx9Sq+Atvoobjf2XYep3riZyBmj0HXvHIc7+8GyTjmvIEjojDCm6aKkAKOasH6sLa1kYjuFhUGWeSE9hQu3HCTH7gzwbflnThGRWg0TosK4q1dCp1tf9lfbOFBt59c94zHKMv86doJf94j3pyq/ctbFvPbq61x19Sxy8z6i0upNrNcrvgf33j6Nd1f/xK7tOdidbsbOvgl3wT7OmzrVXyvI5wtz1VVXMTLqklaPq8ZVw9v73gbqfFm6Hj6B0LmjELQOCanTRabwYekMTvFTl7VatPExSBoNjqy6GiipqaksW7YsYN+MjIw2FVITCOpj1sgcnjyU14ak8li9nCnX7DjC9C0HOFhtb1e/0Tot/xuZxl29umGSJSI0MpfERxGr01Lh9vB1sZVrdx7hQDv7DxZZNU4ujY8iTKNhm7WG/mZjwP114cKFTJx4Drfc/nt+d9+fufePC9BpteScOMaS5z5hsicarcGERqslKcrEBeefz/Lly1m3bl2ALwxAhKH14uyyFZf5qzJ/ePBDzv/gfO75/h7W5q7tOhYXn15RQ0OxnGrW4TMeqfPfI2FhOc04MjPRxLXfIlKz4wj2vdloYi1EX3Musr7tBdMEgrYQrtUwKz4KALeq8u/jxRQ63OyvtnP/gVw+GxlYVb3C5SZS1/KlJcGgY1Hf7vyulzf9f5ROi0dV2VJRzaJDx9hTZeeiLQd4ZmAvLukWhaYTTPUu1VswMc/uxKOqnBdrCdhusVj47L8fc2BTAZWV+9GbJN547H3efWcJaw8e4P3CQv42fz4v//ADFktEo2UBMjMz2zQmVVUpqC4IaCuyFbE6ZzWrc1aTaknlrpF3cUGvC9rlEHzWI96zRpEQS0JnFaqq4jh0CEu9UgWy3LCeSP303KqqolTV4LFWU/XTfvS9oom5btppG7MPxeHBmWv1fmNrXcVVT2d/fQWnmzt6duOOnt34qKCU/9uXw8aKag5V20kL8+ZheeRwHi/kFjGveyz3pSbSzdCyoI6qJ240ksS4qHDeG96X2b8cItvu5Dd7s3kqs4C3hvWht/n0Fjw1a7y/z40V1c2GYSekWijbojL6gqnk7FzN67fdhmn4cEBF9Xj47XPPseZAERaLpcmyAGsPnmjVmCRJYtP1m3hs02NM7TkVj+Kh2lXNJ4c/4Wj5UbKsWdy75l7O7XEui8Ytont4x9dqagprfjZWdzWJCX3R6gM/O//VQ+iDLoEsdf6SkBAsrSFIH5Lj4EFMJxV1jI+PJz8/3//ct6bto2LFetBIyOFm9L2iCR/fOUUhHYfL0adEIJt1ICFmbmc558ZEYNHKWN0Kk3/ez/VJMUyOjuCF3CIA/pNXwseFZbw2JJWpMZYWemtIvF7H92MH8kJOES/nFnHE5uD6nUf4fGR/YvWn77IlA+vLqxhpab7ysVavISyiG7vWryG+Zwzxs+9ssI/Lo/L5zjwuGJSAUdf6jLaNYdaZeeycxwLarux/JdWual7b9Rr/3vNv1h5by88FP3Np30u5Iu0K0mPTT+mczaGqKlnbf6Ds5/XUlBbhLCvFtXsvvY5WAVAQpkG6cz4jb7mv3rWjNrNsqMx7hNNts0jSGVCt+WxAJTg3aE9JCYY+fQLaTi51/9BDD/nXtB1ZeaDTEDVrfKv6b8la0xLVmwvQRDY+g5XDtMhh7cs5ITjziNfrWDV6AA8eOs7qEivv5JfyTn4pAL2MetyqSp7Dxf/LLGyXYAGvdeO+3onc2D2W2VsPkmlzMmnTPkZZwrivdyIjWhARp4rdo1DlUXC6FMa04PxritBhNMeh1XWj39DIRveZnp7Ayj0FaE5yVFYUlbIaJ1V29ymPOUwXxl0j72JWn1k8suERthZt5f0D7/P+gfcZFjeMuf3nMj1lOuH6U4vu27XpC7KWPUnc0VJ0TgW9U0HnARPevwbjqvbAk6+z+rNPifzt7WRMv65uo7ikdAlC4WMSgqUVqKoaFNGtqmoD9d7UmrbidFO1Zjcx86e3uv+WrDUtoYk0YOwfGtlHBaFPisnAW8P68GRmPk9nFQIwNTqCt4b14cfySq7dcRSr59SrMScadLw9rC9XbjtMscvNt6VWvi21srB3EoPCjUyPtXSIkNbJEpVuDzPiItG3UEpAo5VJG53QYp+jUqJZuaeQYT0i/YUXj5XZ2JZbxsDE9gm7xugb1Zd/X/RvNuZt5LMjn7EqexU7i3eys3gn25ctZkSRGVUjI6veLC6S6v2TVW80iKSq3scn/QGoTgeJWVX0O+mcHgmO9jNjjwlHsoSjj44j46o7iEzpx6q/30PaJ1vpcbAM7nmCzZYnOd4fBgyUUcNCxMQSIsMIVSSxJNQ1UNTgJGfSRERg37cf09Ah/rbG1rRvmH055Ss2EH3deW26EDdnrWkNOwq3M6rfZLRyw6/FnpI9FFUXMbXnVGFlEQRwUVwkz2YX4lFh2aBeaGUJU+0N3hWk1JgDwoxsGj+I53OKeD6nCJeqsjTTK84fTUvmth7xQTlPfTSSxPXdg1ugMTbcwKxhSXy/v4ic0hpGp0ZzsLCSmUOT0GmCG7QpSzITkycyMXkixbZiPjv8GSsOr+DytYcxuJ2n3H/2qO7E3DQPU2w3JJORHj0GMSQqsdF9r3rkbY5c8xP7n3mMpM1ZxFhVZm2BWVs8bBhRc8pjCSri8tYoXqdbsSQU8qgEx8JiGjYM6zcrMQzoj6xvvLKtqqqU/3cDMfMvQG6D2ICmrTU+FEVBbmameLw6jzhrNmG6MFweF07FiUtx4fQ4yazIZHTiaA6WHWRAzIA2jUtwZjMswszRKcPQSZI/P4nPIuFQghdiG6bV8ECfJG5OjmPJkTw+KvTmAXrjeDHXJ8ViDvINvyM5b2A37C4PmzPLSLAYgy5WTibOFMdtQ2/jV0N+xf6FXl+WimsuwB0XiYKKKoEqeStEqXLt/6goUt02JAml9jNOHzmDi0ZMadMY+g6eRN9/fYnLVsPer96h/NXX6JZZzsD8rvO5ndVInZ/sTwiWVqCqwRPdEdPOo3rjJhS7DX3PnhgHDgzYbv3mZyKmZbRZrEDj1hpfBMKe3duwlVUiaSR8r+ZktTxy0DhqPA4UVUGv0WPSmojURKKTdQyIGYBBY+C7nO+EYBE04OTqy/paPw1nB1zhEgw6nk9P4a/9upOxfg+Haxz0+WEnG8YNOu1RRKeCUafhnLTTm/RRkiTQaMDjYdTvHkKX0O20nh9AZzIz/IrbyPslk4rMT4hzhshn1tl34xBHhDV3EVQV/8zxVJF0OsInn4NSXY19//6AbYrNiaeiBkNKy2vhrSE1NZUFCxawYMEC7NZqRk+eQkZGBnPmzGl3Mjmnx4lbcTe6bCQQ+NDX/l6cbVwS2l9t429H80k1GTgvxsLk6PAmf3vxeh1P9e/JvQe8xRknbNrH16P6k9HBzrhdHn80TOcOI1QRS96NEwo+LMIW1wqC5XQbgE6H6gqMCqj4chORM8cG+UTBpX90f77M/BKXp/XRR4KzD7+FpQ1LQjaPwu27s/m62MpLuSe4ZscRRm/Yy3+LypvMsHl991i+G1Nn8bts26FTG/gZzvH77wffZxLE5bp20dnT9QaE3IBCClnqfB8WIVhagUrwJyOSVovqCEw7rjpdaCJCu3Jtn6g+XNz7Yr7J/oYaV4g5ywlCBp9gcbTBwvJxYRkHawJ/E3kOF7fvyWLhoeNUNxFxlB5u4g+pCf7zba1XpLEzCOUSGdb//q/uSQuRT2cvwsLSGMLC0kXwRiMH90ssyTLuE3WZLZ355bgKa6jasCfggud7nJGRQVRUlP+x7+LXGRdCnaxjZu+ZfJ/7vbC0CBpF56skjDfZlFtROVRtb7YWiab2J5YRYabgvAz2TBrC73p6fSzeOF7MlduOUONp3CpwX2oiSbVZdT8s7JyinCcLldTUVJKTk/2/z2XLlgU8h9P/+5XNdctlNZs3n7bzNo6waHQlJDq/lpAQLK0gWFFCJzP897/3X+D6T8jgXQ4z4brLyMnOZtGiRSQnJ5OTk8PatWs5cOAAVquVr7/+mh07dvDWW2/5+2nqQlhRUeH/ghkTIvjg3bcptZayeX/DC1VbZ4WyJDMjdQYb8jec0nsgODPR10uO5lJVHjmSx+Sf93P7nuwmQ50HhXlTjuXYHaiqSqxey1/6dec/Q3tjkmW2V9Zw4ZYDlDgbJliTJIkbkrwhyJ5OvqgeO3aMtWvXBrQdOHAAu71zCzkC9N/8s/9x3h/uQ3WeenjzKRMqPiOdbT4IcULhYxKCpRWoQcrD0ljH7vJytFotRUXelOaaKG8GSpvNRl5eHqqq8sUXX2C3e2enq1evBiAzMxOdTseuXbuavBCazWby8/OxV9uw7ati7JiJnMg/gUZ7amnBfehkXce8L4Iuj67e1c2lqOyp8lYW/t+JcqZt3s/+aluDYwaEGdFKUOrykGmru5HOiIvkxfQUwjUyh2ocjNu4l8eO5DUIme7sb6JPqHg8Hg4fPgxAUVERa9asweFw4HY3FFp79+5l48aNAW0daXWRNBrMY+v85Gw7d3bIeVpDZ8/WmyQU7swhSmd/ZEKwtAKlYYLa4CDLPPb00yiKgupbn1ebd2vy1O6nKAputxul9qJdVFTE3//+94ALXe/evVm+fDnvv/IW+h4RzPvNfCRZIjUxNWgvQXjUCxojQLCoKsZ6/hKHahxctf0IuysDfaBMGplJUREAfFhQGrDtovhIvhrVnxidhiqPwj9yirh066FOt6Y0hc8iCrBx40ZUVcXj8ZCXl8fGjRsDRMlPP/10WpeFdElJ/sdqZzrehuhnJ2gKqdMX8YRgaRUqcgfclyW9HkmrRZIk7E4na9euZe++fQ32a6kekG/25jzJvDt58mTGjhrD/z10L7Mvnc25F5xLau9UYsJjgvo6imqKgtqfoOujkeosHi5FRam91C3qk0R6mJETTjeXbzvMCWfgd/vG2syy/8kraRBhlBZmZM2YgSzs7b3h7qi0cdPOox37QtqA1ynR+zpdLhfl5eXeychJN2af9aUzUF0uKv77X/9zSdtyNe2OG4xvEKEx6fF/TiEynlBDEonjugYd4XQLNMg6e2jvrnb1U/9CuWzZMqKionC5XBgMBpbc8xeyj+VwyaWXMPnCycyfP59+SSdXAWl/4cRJ3SexuWAz5Y5y+kf3b9f4BWcekiShlyUcisrsrYfIsXvFdKxOywcZ/bhg8wEKnC4+P1HBLcl1ydMuioskRqehxOVmm7WGcVGBRfq6GXTcXRsRtDQzn+9KK7lx51ES9Tp2Vp2eqLX6+Y18ZGRk4Ha72bNnj79NVVVUVW0wkfDhm2gYDKcvcZqk0xF/992cqPVXK/7H/yN6gBMZ37JyXWJJ/4279n9N+gUYZ/8uaGNxZWcHra9g4Dh4sLOHENKEgowTgqUVdJSojI+Pp6SkxP+8uqQIt8vV5oyCJwsNu93uT8lfte9DXFWlFOz7Aef0NHrFT21yLO0pnChJEmOTxrI+bz0J5gQiDY1XqhWcfSQZdGTZnH6xAtDPbCBOr+XWHnE8fjSfv2cWcGNSLLpaE6ZOlkgy6Ch1ebA1s1xxd2oCP1dU822pldUl1oBtliD5aJ3MwbKDHCo7hMPjILMik5+O/+TfVumsBCAnJ6fFfrKysgiLsPD2+x8B4PJ4oPQoHF4NtnJczo51zo37zR1UfP4/nEcOE8kqIlrpDKz+/C3q+TcimYJTpNFWK+5UhyMo/Z0q5e95s4SrjfgaCbx0dh4WIVhagdIRiePwFiv85ZdfkGUZRVHILq0C2m9683g8OJwuXn7l36gqHNu6jrBLRqALjyE5fSo93UfQN5Gh9lQLJ45JHMN3Od9xYeqFbR+44Izko4x+bK6oRiNJ6CRIMugZHuGNBLq9RzxPZRZQ4nJzzY4j3Ng9lmSDjm+Kreyp8t5AtS386J4e2JOPCsv8S0cqYJJlrkoM7pKnD5PGxJC4IRg0BnpH9mZS8iT/Np1GhyzLhIeHU1pa2kwv3t9pZUU55507hZLCPGpqanjry/Usfu4/WA9vIjMrm5deegmgw3xbkh5Zgvm/UwPa7PQHPCiYUet5C6hOG+H6g0gyqO7giQvZYEBxuTAOHhy0Pk8FTWQknooKIi+9tLOHEpKIJaEuQjBT89dn4cKFvPLKK/4LnE6rwelyt/tLoSgKDruNYel98DgrSOg/hKG/ehL+ORIkieSRt7Bj9QMMu+BvSHKgGGmpcGJL6GQdernxgo6Cs5MeRj09jI1/J4wamRlxFr44UcH68irWl1cFbO9vNjLK0nwSxQSDjjt7nb5aOCadiRM1JxrdZtAYkDUyVfaqRrefjCRJZGRk0KdPH5555hlsNhu7d+/moT8uatNEob2YR46A/wa2GaldEonoDndvB613qcpdlA8v1NY80wXxN+5LuTA4PXh9BgFDWsMlc4E3UlY43XYBVFXtkPU7i8XC7bffTnRUNADO2lT97dVGsiwTbjYyfPAAtm7+mceeWoYsy35flLjIFFLGL2DPuqWNjuX999+noqKCnJwc5s+fz/bt29s0w9PImtANVRSEHPelJnJDUgxXJkQzONxIH5OBZIOOuQnRfDtmAKZOrr58cm6iMF0Yc86dE5DfyIfb5SbMHMbAtIGcTGO/Z0VRWb37CCs37wAgPz+fmTNnsm7TViwREQH7dliYc8YNJ4/U+19lHtTULVVTLzmkJAfPSdf/HsodL9AEp04o+CILwdIKVDruw1q4cCGjhk4EvLOulJRBgITR1PYLg0GvIyIyGruqJy6pF0hSA1+UKEsy8elX8Msn8ygp2tNMb21nePxwPj/6OYdKD/HhwQ/ZcWIHitrJ9UoEIcugcBP/b2Av/pmewrdjBrJ+/CB+mTiY59NT/D4tncnJCeCMGiNZh7PweDyN+nuFh4eTeeQoen2gFaJxDa+ya9V/+eNt8wCIiooiJyeH8DAzNpu9gZXlpZdeCr5omfMCLMqDBwvhL6XePx+auteg1ne+D6a4qH1jpNNgURIECZHpNvTpqCUh8Fo2Vq75Hzdd/Wt0Oh2FhVloNBrstoYROo2Zio1mr9nWZDJy/wN/Yt68eSxfvpx169axe/du5s+f3+A4vSkGLN2JiQ+OKbbcXs7mgs0cKT9CVkUWPxf8zBX9riAlIoU1uWvIrcwNynkEgs7AZ2nxRQpGRUXxzDPPcMsttwT8xnp0j6O6phqLqeWon5SUFKKjo1m0aBEA0dFeK2teYRE2Ww0FBQVs/GldwDEdIlr0YaAzeoWIp140Uz3BglKvvSOqtIfC1F3QIm0NBukIhA9LK+joZQ5Jlnhs6RIKS47z04Y1RMXGctUNM3ntpfepqalBliWMBgM1Nnvt/jKqomCKiab3sDFk/vwDN10xhcWLF2O1Wpv1RampKSbrh6UMm7ak3aHaJbYSXtrxEnEmbziqSWsiNTKVcns5/zfi/+ou7MYopvacysa8jfSM6HmK75JAEBr06tULq9XKu+++y7fffuv/jQ3ubWTHLi1lrQivzs7JAVVFo/VegrMyM4kID8Pj8SDh9Uc7dPAgGRkZFBQUAFBSUsKaNWs67oV5mhAmnnpRM1IHzHE7u2q0oFV0ueKHL774IsOGDcNisWCxWJgwYQJfffWVf3thYSE333wz3bt3x2w2c9FFF3HoUMvl3j/++GPS09MxGAykp6fz6aeftv2VdCDeJaGOnQX07JPAN6u/4OfV3/DNh2+RcckIXvvuNeJiY1AUlRqbnTGDe6PRyMi1ZlmluobbLr+AHkmxYPYm3GrOF0VVFHIPf43rxF4O7XqrueE0SmpqKg8+/iD/2vUvHhjzAHcMv4MX57/I0Q+PMqXHFC7td2mD90n11jUQCLoc9fMb1Uer1ZKamsqf/vSngN/YE48tISZCx6O/mk50bTRUk9T266kNoVVUleoaG4qi+n3Zso7nU1BQgMfjoaSkBLfbTVZWVlBfY5PUEya+MF9VIbjWkNq+1FBbNu7su7KgSdpkYenRowd/+9vf6NfP60X95ptvctlll7Ft2zbS09OZM2cOOp2OFStWYLFYePrpp7ngggvYu3cvYWGNe/xv2LCBa665hiVLlnD55Zfz6aefcvXVV/Pjjz8ybty4U3+FQeB03nPTJ5wDwDAuAGDu4Tn87o7f8canb7Hj0DEiLUYiunUn99BRRo0eyajhsRw8fKx1nbuqqa7KJ/2K/6DXh7e8/0nY3XaOlB/hvbHvtfoYFVXUGxJ0STQajT+9Pnh9VVzOhku1vkRyU6eEoTPH8uSHm3CpGn+6gtZysjiSAMXpodxajtvTiblBai0vHXYdbKIYpiD06FJ5WC655JKA54899hgvvvgiGzduRKfTsXHjRnbv3s3g2rj6F154gW7duvHuu+9y2223NdrnsmXLmD59OgsXLgS8Tqhr165l2bJlvPvuu+15TUFHUTsmNX9r0EYZ+fury8guP8769evRGwyce+UYfvjIQ3r/BKZMuaXBMarHiSpJyLIOe/56HMfWIWl0KG4n9qgIwiOSGjlT0yiKwtGKo7gUF+O7j2/Tsd5K10KwCLoeMTEx/Pzzz0QYwzmee4xr51yNqqocKT+CxdUwedqcKx4lO9vrr2WxWIiOjg5IDNlmVKiotgaohPLy8vb315oT+qj/m/WLruD+jiWpNkxWWDS6BKGQh6XdC5Iej4f33nuP6upqJkyYgKM2W6HRaPTvo9Fo0Ov1/Pjjj032s2HDBmbMmBHQduGFF7J+/fpmz+9wOLBarQF/HcXpWBJqDovFwooVK9iwYQM//fQlv7/8PFZ++jRPzOtHSnIcf7vvcqxbn8G69RnK1z3A8PTePPjbS6jY+jSKvZzIMQ9gGXkvEaP/gEfXdrelZ7c9y+qc1UToI5rd7+QwULfLzqiMEfzrqVfbfE6BoLO59tpr8bjdFJWd4J/P/5OjWUe9JQfQN5qj6Nix4/7HVqv1lMWFR/Gg1WpPS16WhtRd79SOsoD4TiF8WLoEktQFnW537drFhAkTsNvthIeH8+mnn5Keno7L5SIlJYWFCxfy8ssvExYWxtNPP01BQUFACODJFBQUkJCQENCWkJDgdzRriqVLl/Lwww+3dfjto6OqNbcBo9HIkCFD2LZtA337DiU6ejzKwNlI+g8x9jgXy8gF/n1l0zcYksYTOfLegD68Jue2vZDXd73O5O6TGZ00miflJwPM1qmpqdhPSuv91FNPUV5ezuLFi/n8xyXYHRV0czVeS0UgCGUWL15MzoEs/rfqCxwuB5MmjyPfUYjW7hURvrpdTeGrrH4q1NTUMHnQUNbta1+dsXaz8Z+1jrcSmtzagqxBvwb6Ouzs26Cgq9BmC8uAAQPYvn07Gzdu5Le//S3z589n79696HQ6Pv74Yw4ePEhMTAxms5k1a9Zw8cUXtzhDaMxRsyWLxsKFC6moqPD/5eZ2XOis1w8jNBgxYgIudwVW607kNoYYehPgtf6V/HvXv0mPTWd00migYb0hVVUbTUOuKArf/LSU8WmXYjZGo9d0YkVYgaCdWCwWPvriE04Un+CKK6/kg08+AxdcefuV9O3b179fY4VDweucGwx+yWw5cCEoyLo6Z9vVi2Hln2Hlg2j3eR30VaWDroKhplc6e90jRJHo/CihNv+i9Hq93+l29OjRbN68mWeffZaXX36ZUaNGsX37dioqKnA6ncTHxzNu3DhGjx7dZH+JiYkNrClFRUUNrC4nYzAYTluVU6WDqjW3B1X1IElatNr2FSDLL93IDwe9Dnw6jYkJfW9uct8yZ1mAz0r9ekPXXnstJ06cCHhf8vLyMBqNHCvYwjmDXyYsqjaUuSNCIQWC04TFYuHDDz9k37597KrcxTH5GO9e+jqTJ0xj6461yFoPDz745wYOtu4gFdGzOevq9zRn0Tll9Ga45DnI/qn2pq2CquCxVlD1wzpqrHG0zfutdYSKPPCPI0Su9aGGd0moCzndNoaqqn7/FR+Rkd6KvYcOHWLLli0sWbKkyeMnTJjAqlWruOeee/xtK1euZOLEiac6tKChdlDxw7biclkpKVlDXNz5aLXeqKvGZncuV8NIBgCd1sBV414DIM+ayc+HX2r2fG4l8IJbv95QdXU1RqPR/1mDV9Qpihuj3uIXK96xhMCbJxCcIr1792b16tVcMfkKPn33OcLDohg5/FySEwfy5JNPIstyUJaBTkYjy7gVb7+pqalB7z+AkTd5/+rh2rePvCeuQBsf5KKSvotqqPmwhMLFPgQJhXelTVPfRYsWsW7dOrKysti1axcPPvgga9as4YYbvDUpPvzwQ9asWcPRo0dZsWIF06dPZ86cOQFOtfPmzfNHBAHcfffdrFy5kieeeIL9+/fzxBNPsHr1ahYsWBCcVxgEvJ4fnftxqapCcfFqunWb6Rcr0HCZ5uRU/E2x/9hHTE+/t8ntHx34iOm9pge01c/x0qNHDwwGA/fdd58/+6Yse9ftu8UNrBtLVra4AAjOCIxGI4PTB5Mamcq11/6BmppKHn74YSIjI1EUJahixWe51Bm03HrbtciShCzLTJ06NWjnaC2qT1DIHWQpDRXB0tnrHV2BrrQkVFhYyE033UR+fj6RkZEMGzaMr7/+munTvTe2/Px87r33XgoLC0lKSmLevHk89NBDAX3k5OQg1/viT5w4kffee48///nPPPTQQ/Tt25f3338/ZHKwgC81f+ed3+NxUFT0Jd26XdTAb6X+Mk10dDQPPfRQq6IKtNpwwoyNL7vlWHModZQyN2Fug22+nBMA4eHh5OfnM2TYEIYMSsFkMlJWZiU7O9tbefahh9BoZEJDmwsEp45vGTopKpnY+FgO7DvMpk2bAG8YdGM+Xe1CVdFoNUiqzFdf/EBiQjc8nXWz6CjBEmoWFr9gEderxvCHoXcibRIsr732WrPb77rrLu66665m92kstfTcuXOZO7fhzTEU8C23dJaRwOEsprxsEwkJM5Hlhj479ZdpGkvF3zSNf/WW/bIMt+Lm3lFNW1/AuxTVu3dvli9fjkavxVUi4XIpyLLMO++8U5ey/MghYWERnFH4RPvAQans33uIHTu8FZeDJlbw/mQizUZuueRc/njTbKbc9heu+9WdHVO1uSVqBYXUQYJFVYK/jHZKiMtVo0h0fJmalhC1hFrAXZuDQNNR5tAmUBQ3JaVrkSUdCQmzmtzPt0xTn/nz57frnHaXHVmSuW/MfS3uGx8fz5AhQ5C1Or5dtZJvikpwetzEx8fzm9/8xn9hnX/FhVBd3K7xCAShzKw55/HZx6vIzs4Oet8GnQ6dKZzwfmMwTbiB3OJ7Wj6og+ioJSHfspfqCS0LS6gEWIQcIfC2iPCNFnDX2mF1muB/Wqrqobx8CyUla1EUJ+UVv1Bc/D0lJWspLvmW2JhziI2dEvTzAlwz7SF/kje7286zvzxLn8F92Pvu3lYdP23aND744AMunDCF1MRkulkiMRgMAWIFgNKj/jpHAsGZxOxZ8wBITw9O1XMfkiR5C54ajRQVFdVWg+7ES7VvVh3sdfGQXRISNEVnv0VCsLSAq/bHpO0AC8uRI3/Hbj+O01lMQcEKjIYk4uLOIzb2XLrFX9joElAwqbBX8Py253l91+vcPORmupm7kRiW2Oi+viy2vqikhQsXYrPZWPTYX8k9UcCgbuEBuSn8OGvA0hHBkAJB55IYnQxAZZU1qLNyCXA4nWRnZ/P2228zZ84c+vZM4qWXXuqcJaFaZ2Ip2OkJfNfUDoisOiWEhaVRJDrd51YsCbWEy10rWDrAwtKv3wOANwKopGQtlZV7cLkqqLFlotWEoaLicpYQHjGYiPCBQTvv9uPf4fS4OVxxmEXDFqGVNFRW56Mobuyuaipspd7cKbU/XEVxoageapxWLNFmDmbtwyaVktwjkVG94vno+y0MVGv4+Mv/ACqewl1oyo+DRgumqKCNWyAIBeqnEtBoNByvl5I/GCiqiqp6c17dc889zJ8/n/mTksmY2/JSbUegOL2Zqp1ZWRwYN84rXCTJ+yfLXt+W2sfIsle8ndwugX9NofY/T23pgpDxYfGZD4RgaRRv9fLOHYMQLC3g82HRd6BJVpJk4uLOq81pk0+38IuQJO9FsbDoc8LD+gNQU5OJ1boLnS6qyaUij8eBRtPQMqN6nFTteR1bTRHZpbkY0dDdVsWBzS/g8TjQ68NwOazUFB+kZN+nSIoCkoSKipr9DS6Pg8LKI4yckM6H735ExuRUqqqtrN9VgSyDftr5eDxVOO0FOPVRWFLOBWP7ktsJBKHEtqJtVLuqkZBIDk8OSCUQHx/PiRMngu6MqJElYk3akLiZe+o5EysVwa/ZprGExnVCJI5rnlB4V4RgaQGXp+MsLCcjSRJGY3f/c7s9F60mDEmScTiKqKo+SGLipVRUbMPhOIHBEB9wvKqq5OT+i9jYc7FEDPGO35pNzYF3AZmw9BuJCOvOZcA9pm9JTJnCkPF3+4+XtS8QkzSCPiN/FdBvmXUXBq2Z3rEjuPWPt1J94tfc/6snsNlszJw5k/CsLAwxfdAnjsNa/C1JSYFVvQWCrkyNq4Zzks/xP6+fSmD69Om8/fbbQTtXSkoKUVFRZGVlsmBSIn9cVJuzqhNnttp6Wcejrr8ePB5Ujwc8blS3BxSl9nltu++5ongddhWPV9A18hq0MTHEtRBZKggdunym2zMdV63TbUf4sLSEydQLVVU4cWI1Go2JbvEXAhAZOYL8/E+IiBhMWFiaf225qvoAMdET8Lirqcn6ClfRdmRzNyyj7kM6KX9LUwnnfAXdfLlWVFVlyh0fUVFhQ1XVgKikwYMHk5GRwWeffYbbXU1+wcckd7/uNLwzAkHnUT+VQEREBEMHDmbX/j0NUvO3h/KyMkyyAdXhwB4/lKFDBnPxpLE8dM2EJjNYdzRSbV4nfUoKSX95qIW9uzBiSahZJEk43YY87loLS0dECbUGszmV+PgLiImZFNCelHQFWm0EhYWf43AUYbPl4HQWYzT2xOEoRJu7lcj024hIu6aBWAHvLHH58uWsW7eO3bt310Yi1CWcS01NJSYmhmXLllGjqMgGLYsfe4To+FiuXXAr7+5ayeGjR9hfnsOnmT/y4k8/0CP5BmRZFDoUnNnUz/h87Ngxftr0E2s+/x/9e/c9ZefbaEskHlVBo7dQ1a0P2vBITCkDyYq8tJX5lTqA2gmRGirRPB2FSBzXLJ2d7R2EYGkRT+2XWO7MVLdNYDR2Jyp6LA5HAS5XObEx52AwxJOYeCn6cxbB/v/BkW8bPXbhwoVMmTKF2bNnM3PmTG8kQr0on2PHjmG326mxVaLXhTOo3wCsJeXYq2qIcRr54C8v4nI4Kd+fR3VNb8KN6fySXUH/9KH86q77+eHgCX48JPKvCM58wsIjmHzxTGZcevEpC5acvONkHsuiV49eLF++nOrqaoqLT/DHv/y+VRmsOwJJW3veUIvmCTadbT4IcULB8CQESwv4cyaFwqfVCEZDIhbLMCyWYYEbJAlG3+otGd8I9WeJOTk5zJ8/n+3btzeoBltVdQLF42Ly5MnIsozdbveHWmq1Wq/fTIWdm0b3ZGCSBZNOQ/coE+f0i6uNdhAXAUHXptRe2qrv8WOPPIbRaDylcymKgtvtRmfUMCRtFIcPH+a1117jwvNnNp424DQgab0WWjVI1adDnRC91IcEnX09Fz4sLeBzMgpBA0vrcNvA7QBt63K6nFz9+aUXlyNLKgaDAb1ej0ajwWQykZmZSffu3UkcOYlZfePRamTCNTKS5I1wkGUJo06D3aVg0nfOzFAgCAbpsemsz1vf5PZiWzHnJJ9DrCWWhIQE4rvF8fOmzad0zr17djJv+hWsMxgYP348v/r1rdx8883EdA9r+eBgo6kVLGeLhUUolibp7OmnECwt4P8Oh8D6XbvofxEcWgWx/aBby7lcfM64kiQhSRIulwO73cmanFJcHgUFCU9tqLdbUTlaWtNkFk6zXkOVwy0Ei6BL0zeqL32jmrZuHK04isPjALy/n/HjxvPLlq3trt4sIWHS61Fx4azNgWIM01JWUNOu/k4VSXeWWFiEYGmWUChZIJaEWqDLf4f1YTBoNhQfgFbkdPA54/oEi8PhRpY1dMv6Do/LidvpwO5R+OlYGQ4FZveLY0hcuP/4+pEMMWF6iqscHfKyBIJQQUZGUb1rx76SFclJSXSPjW/XNEdFBa2GlT//hISEvdrFoc2FxPUIb/ngDsAXJcSZLlgELdLZK/xCsLSA0snVmoNG32lw4EvY9RHs+x+cONBgl7KtX3FzRgRj+3fH5XJRXV2Nx+1Gq9OyalehdydJIkynYVKPaPokJ1Jyosh/vC802kdMmJ6CCnuHvzSBoDOZPGwyr/7zVaDOmT3n2DHyS4u588LLiIkwopFlDAYDWm3rjNpl5eUMTu+PTq/DYNYy6JzuaDvJUnm2+LCIxHHN403NL3xYQhrfxxOqTretxhABgy7xSmTFA4e+geJD3m2DZgPgyNxEgjufV//vIhJ6D+HNd9/D6XRiq7HhcLoACZPR6Dd110+gFR0dzUMPPRQQyfBLdhkT+orCh4IzH1VVURTF78y+a+dObDYbb6xdiSUmmh7JZnYfzGy1YIkwmghPSEGWN3Heeed1bvHDs0SwdH1zescSCnlYhGBpAfVMsbD4kCSvE12/CwAJ9nwKditk/kBixrnQYzTozCyZVEBRcQn/+/JLdEYtN/7pz/zvjf8wf+4VPP/880BgAq3IyEiWLFkSYGFxehSMOuG/IjizkZDY+/Mx/v3BZ2glHd2SonC43Uw87zxmj8ngojkzKD60m7Rzr8JqtZKUlERNTfP+KJUOOz9t/qnTQpnr47Ow4PFmrA0FXwbB6ScUPnYhWFpA6epOt03hixoadjUcXg0pE8Ec49+c0D2Zzz7/nN/fcTvvvPshN06Zwg3nz+Cuu+/xX0TrZ731MX/+fP/jascZPiMTCAAJmaGD+/Gra6/wt0WEhZGWkkJGdA/2fbuKhImzOHjwIAD9+vXjyJEjVFdX1xaUazhtVRSFXr37ERPRCVFBJyHVF01uN+jO0OSQInFci3R2lJDwYWmRLh7W3BKSBGnT/WIlNTWVZcuW+Tc/9tTf8aBw4YUXMv+6q5l6wUWtzgehlRu/GAsEZxKyJKHRBl5Kfc7ng667kqjEqfTo0YP+/fvTv39/Zs6cid1uR6vRNDprjYmJJqVfX4YNG8727dtZvHjxaXgVzaCtEyhndGhzXUiooBEkRLXmkEc5y5c1LRYLqX16c8kll3D11Vez6Ughzzz6Z7Talk3V0WY91U4P4QbxNWsvR7YWIWskuqVaCIsMzKWTf6SC6nIHKUNi0Rk6f+ngbCU6Kpbi0sadz8sKqokf2BuDoe6zW7hwIa+88gplZWVoNBo0GtWbZFFRURSVgQN78c3KDwkPSzvtr6Ux6l/7zlQ/FseRI/4soWLJq3G8b0vnKhZhYWmBOj+ss/tLrNFoGDJkCMN7xvDZ2l9adUxJtVOIlXbicSvk7C0hKsFM7+HxVBTZOLS5kKJsK06bm0NbCrHEGumTEUfWTlECoTOZMPoc3v/w3QZ1uRRFpSy/hvieEQH7WywWbr/9dsxmMyaDlj/cfiXjB/VFkmR0Oh3Tpl1ImLlfJ72ahij/v733Do+jOhf/PzPbVVa9S5bcbdmW5Ypl44ILxsbGDhAIEHBCu7m5JLFJcu81X/gFwiWESy4tNyG5gWC6gYCpsWOabYh7kXtXs2T1tmq72t2Z3x9rrSSr7Uor7Uo+n+fRo92Zc868787uzDvnvMXWmppADvb/ElV/UPvJJ+7Xcoh/wscDnUC4A4q7SQ+4w5r9LMeA0NwAqgL2Jmiqad2uOsFhRbJZGDssjgMnd1PbOAVJbv1cJMnl5SNJrf4+ImFc7zm2vYhxsxMwmFw/0cTR4QBYKpoozbMwalqs24jWm7QoTgXZn5EkVzA/vm8tFXXFHZzPqy42kJrReZTc+vXrOX36NJ988glP/fE9zEEGEmJjsSsKGo0poB6Q3LMqGk1AyeVTLukYsngRssnkZ2ECF7EkFOC0nKBBH9bcE6UnoPYCMk7U+nKoPOfarqrYmxqgoRLKz2AGFifUkVNR714uAxVVdU0WqqorskoFpqVG+EWVwU59tY3gcAMabcfvnDnahDm6/QU1YVQYxedrSRojPm9/EBoS2sH5fNGsG4hNDe0yHNlsNvPBBx8AUFOzn/p/fkvSkh8j6fX9Lq/XXPJbkQIgYqm/UC9dzPQpw/wsSQAjCR+WgKclUc6QtVfqyyHvG4gcDmOWEhOfTHGT1hXezKX1+MISCEuClBkAjNLoILQZQuP8KfmQpOBEJZIsMWparMd99EYtdVVWSnJriUkORaMTMy3+xulQ0Bs9u7yGh08n/Prp/SxR73E72nqYQ2ZQ0vpk6l85AphASBwnrmw9MORnWPK/hejRkDgFaE3Nf/l6fDtix0P5ST8IO/RptDSTMi6y54aXMWpqLEFmPecPlVF4urofJBN4g+JQ/C2C77i0XDKUZ1jcDreyuCV2RSDcAsXZ6QF/T4H1OxO+48p42+S6ybWkFl+xYgXLly9n9erVHcOYtQZwDs1ogYGgq1Dv8oI6wuOC3O8vDzEHyMzM7DTMVavXYI4yMXJKLM1N4twMJE319nbvrQ129KahMxvRMsMylG/m6qVaUEhDV0df4O/74dD5VfUTQ6aWUHcMnwclR2H4vI7J4JyOdsng3KhD6Amynyk+X4viUIhICKY0z4Ikga3RgcGkxWFXSJ0YhbXBjt3mIHF03/xQNDqZsBgT+ccqSZ0oyiIMBKaQ1jwltiYHF05WebWkF/C4p5mH8M1cEUtCPeFaEvIvwmDpgSFTS6g7gqPB0dx+m6LA3j9D9JjOEyrZLAMm3mDF6VTIza4gfoQZY7CO6pJGkkaHu6J6Wj2WKThWSVN9M+NnJ/rkuFFJIdRViqKTA43D7qTgWCWjpscOrWgafz9WDwRKywzLEDpvPiYQvtPCYOmBIVdLqCdsdZCzDWQtTP4emFxP/Glpaaxdu5a1a9e6m2ZmZrJ69Wr/Z+IMQI5tLyQkwsjwjGi3E2zMsNZ8HHKbJ7m0jGifH98QrKOh1tYh2Zyg/yg4VsXIqTEBcWHvF4aqXgDu4IohPIvkA/xtu4qz0wND3ukWoCrXZZjYm+DU32Hs9TB2mdtYEXhHdUkDquoyRPoSsSPLcgd/l5aU7z0RP8JMaa6YBRsoLp6tISIhSOTCGaSoLTMsQ3nZq4+IKKFBgDus2c9y9Cs1BRCeAic/gYk3iR9tH7DbnFQWNTBpQXKfx4qJiaG4uNj9vm3K956QJAlJrMcPCPogLUFmPRHxQzML7BWB8GHpESkAnFjEnakHWpc2h/AX2Vrrqtg84UbQdL5KaLfZqCq6MMCCDT4KT1ej1ctcPFvT58KPHoWYd8NQ/soGEvHDw9pFdwkGIaoIa+4JKQAe2706Oy+++CIZGRmYzWbMZjNZWVls3rzZvb++vp4HHniA5ORkTCYT48eP58UXX+x2zA0bNrieBi/7s1oDw2nQXXDc/+eqf7iwF/K+dS0BdWKsOO0ODm3djN5gICQymtzsA5z85mvK83M9Xp64khieEU3apGj0Ji1n95f2aSyPQsy7wGlXOlQQFggEneNeEhI+LN3ib/drr5xuk5OT+e1vf8uoUa7CXK+++iqrVq3i0KFDTJgwgXXr1vH111/zxhtvkJaWxtatW/nxj39MYmIiq1at6nJcs9nM6dOn220zGo29UMf3tIQ1D1kflpSZEDmyU38Vu83J+UPl1JQ0ExsXR0V1NcMzp1FTUsy5I4fIzcnxg8CDg8iEIGyNdnKPVGAK1RGdHIJW513irQ4h5tB5iHknSLIrdFog8BXO2lpyb7m1dYPU8q/lRZtrpCR18b9t967auP47a2qIuvdeZJMRtFokjRZJp6X6nXewnTwF2ra1jVz/VUUBRUFVnK5lHkVxb+vqtaooqC0FHofqdd4XSF3nkBoovDJYVq5c2e79E088wYsvvsju3buZMGECu3btYs2aNSxYsACA+++/nz//+c/s37+/W4NFkiTi4+O9l34A6Cyid8gR3DFfR7PVQf7RSsbOjCckfBIZWyfy+uuvs3LlSsyhofz6hT8iSRLOIVpuvq/IGtld26fR0kxpjoWmevuA5eeQNTKyZkh/a4ckjhob9ov1SG1mx1S7gj41FE2If+oMaaKjQacDux3rkSMDeuyLv/zlwB1Mo8GYnj5wxxtkBIALS+/Dmp1OJ++99x4NDQ1kZWUBcPXVV/Pxxx9z9913k5iYyLZt2zhz5gzPP/98t2PV19eTmpqK0+kkMzOTxx9/nClTpnTbx2azYWtT9txi6a+IiCssrPkS+Udb80kkjxvB7atupry2ol1F2jOnTlJRkEd1cRERCUn+FjlgCTLrCTLrKTpdjbXejrFNorH+RlVU4Xw7iFDqm9GnmtEEt35HVFXFeqoK03j/JALURkQw8pOPsbU4fLcpeur61+Y2dum12sk2d792T+mXjXHpf92XX+EoLXUFPTicqA6HK+Ouw47qcKI0NZHw+ONIOm37vrIGSSO7Agdk2eWT0u61xvV7aLvtUhVqOSQETVhYXz+uIUsg3AO9NliOHj1KVlYWVquVkJAQNm3aRPolq/SFF17gvvvuIzk5Ga1WiyzLvPTSS1x99dVdjjdu3Dg2bNjApEmTsFgsPP/888yZM4fDhw8zevToLvs9+eSTPPbYY96K7zUtzuP/PFdBsEHbpfOtqqo4nU4OZ2dzw8yu5faGizY7O9FzVXyMR+2P1DWxu7ae2xKiyAw1MczUuxwcF8/VsPjmq1i3rjXvyjXfXcZ9v/g3fvrTn/L4448DruUJVVE4f2CvMFg8IHFMOOcOlDF6+sAUjUxJj+T4txcJCtWTmhHVZeVgQWDhKG9ENoS6Z1kkSfL73UKfloY+LW3AjmdevnzAjiXwHH/nYfHaYBk7dizZ2dnU1NTw/vvvs2bNGrZv3056ejovvPACu3fv5uOPPyY1NZUdO3bw4x//mISEBBYvXtzpeLNmzWLWrFnu93PmzGHq1Kn8/ve/54UXXuhSjvXr1/Pggw+631ssFlJSUrxVp0daTtDcMTGYjT0/GecVFFKrmpg2uu838FHAiYPHuCbK7FH7EUEGlkSbidXrKLDaemWwKIqKtd7e6fUxOCyUgqNnqa+uIyTClQRNkmW0uoGbMRjMSJI0oDVmdHoNE+cl0dzk4OLZml4VVRQMLLqEEBzljdiLGxgzd5I7WWPLLJlI1ijwFxLS4FsS0uv1bqfb6dOns2/fPp5//nmee+45HnroITZt2sT1118PQEZGBtnZ2fzud7/r0mC5HFmWmTFjBmfPnu22ncFgwGDo/yye3jrdTkiN41xRuU8MFoDh5mD+eugYd0+Z2GPb1EsGyp6aekYHe++0rCoq5/aXMiKz8xkdSZZISR/JN29/QmRSgtuvx9qoIS3T68NdkajKwP/k9SYtxmAdxedqSBgVPuDHF3SkbeboltcbNmxg9erV/OqR/4/MiZOpqanxt5gCgRtpsDnddoaqqthsNux2O3a7HfmyOHaNRoOieF4oT1VVsrOzmTRpUl9F8wnusGYP2x88f5ETF2sZFpvH+GFxhIeY+nT8JSNSee3oKa/61DsVInXen9rzh8oZPjkGrb7raBatXseyH9/eblv5hToKjlcSHheEObpv+g51IuKDqbrYQGTiwCYZi0kJ5ey+0l750KhOheYLdQDoYoOQg8SMWr/SzbKzQOAvBp0Py0MPPcSyZctISUmhrq6OjRs3sm3bNrZs2YLZbGb+/Pn88pe/xGQykZqayvbt23nttdd45pln3GPcddddJCUl8eSTTwLw2GOPMWvWLEaPHo3FYuGFF14gOzubP/zhD77VtJeoXs6w3HHNZIxamcff+Zadp4v5+Xey+nT8j0+fZ36qd1lTe3NZK8mpJWFkGDqDy1jxJi18TIpreajgeKUwWHogJNJA4cnqATdYAIZPjub4txdJn5PoPs+e4KyxgQq6uCCsZ6rRDzOjjQyMtANDks5+wLLU6lAnEPiBQFgS8soLr7S0lDvvvJOxY8eyaNEi9uzZw5YtW1iyZAkAGzduZMaMGdxxxx2kp6fz29/+lieeeIIf/ehH7jEKCgrapRuvqanh/vvvZ/z48Vx77bUUFRWxY8cOZs6c6SMV+4Y7rNlD6zIs2ITBYOCR783DpJVobOp9ArzS+gYanU6Gh7f3YUlLS+O5555rty0zM5NHH30URVV7FYJta3QQHN66xOZtWvjqkoZ2FYgFndNQbfNbuLFWr2Hi/CRO7ymhodbWc4dL2Isb0CWFIAfpME2Mprmorh+lFLQgSVJr8VW9jPVUNc0NVuwVTahO8VsT+IHB5HT78ssvd7s/Pj6eV155pds227Zta/f+2Wef5dlnn/VGjAFFvSys2dOqxQa9jlvmTeJ/PtrLI9+b16tjf3A6h3+ZMsGrPmcarYzohbPt5bMpCxcuZMOGDaxcuZKIiAgeeeSRbtPCWyqtpE3yfdXhQMR6trr1abfli9H28+vOurU5seTUcu5CFzf9tmuQnb32Ac76Zhz5FqzGnn/+qlNBGxuEfGmZUNLKaCNNWM9UYxgZjiRyvXRJd34qsizz9NNP8+ijj6LRaFBV1T2DOWXaFC6WFhMcHOx+aDAMM2OxWMgrKkAbYaTpRAVBkzyLHhQIfIEk+b/44cCFLAxS3BmbezFvER0WTEJ4EKqqel2LaNOpc8xOjO3gE9QTEVotu2vryW2ykWjUMTbI2OOxLZVNmC5LSrV+/XpycnLa5V3pbobFH86kfkMF49jeRdwYgQmD3LDTJ4XgrG+mMbuMoMkx7ZKcCVopLCxk+/btPPfcc1gsFn79619TV1fHqVOnUBQFnU7nSg9hNPCLn//c1akqB6etiRpLLYZmK3/84x87PDRIGgl9cii2vFoMaSJviGDg8LcblTBYeqCvtYSsdgcHzhYyfYxnIdd2p5MXs0+QFR/N5ATv83XEGXSsio1AVVUKbXY+Kqvh6ohQovVdn+rqkkaiLvOp8CYtfH21leCw/o/YEgQOmhA9QZkxNB2rJGiyeNK/nLS0tHbBBrW1te73qqpiNBppaGgAoK7J6p7h/PX/voEsSzidCkqTgiRJzJs3D7PZTFhYGMHBrt+pNsKIs9aGo8oq/IkEA0IgFAAWj0Y90NdaQg+snMXx/HKge9+TFjYcPcVd6aOZkZTQ5ZieOMRKkkSKUc/quAiy6xo519i1L40EhET07qKnqirF52uJGRbaq/6CwYukkTGMDMN6rtrfogQ0hYWF7X6vTqezXZbutvtcCShdho2iKDidTnQ6HRaLhQsXLjBu3Dj39cKQFkZzUT2q3fMoTIGgt0j4f4ZFGCw9cVktIW+iZwDOFJbx5fEi6pt6dnL89Mx5JkSGEW7q3njw1iF2cZSZZkXlw9JqGpzODvub6ntfdbkkx+KumSO48tCE6FGbFZxeOPEONexWKw01HY22tk6zfRq/zfVl586dPProo1jP1zB5/CSe+PPTNB6r6PMxBAJPED4sAc7lTrfeGAsOh4O/fXuCf712EiGdOMI2NDfjcCooisJ7J86C4mT2mJE9yuStQyxAeoiJccFGPiqr4dooM8Ha1vamPtS2sTbYSRgp1tGvZEzpUdjyLdjLGjGOvvKM19Lcc6BCWe559zanw4EkSVgslg5T6X2ZWm8xXlSHgmTQoIs2ETxlYApqCq5sXInj/CuDMFh6oDUYxHWR8dRY2HUynxMF5dy7bAaxYZ3n3Pj9kdNU25o5XF7FXfExjIoM90gmbx1iW5AliVWx4WwqrebGuAi3TkofQiRFRWABgCHVjL2kAVu+BUOqZ6UkhgqSrCFmWCp6U5B7m1arxWQ0snvnLleby2ZbHH2ocr5t2zb+8/af+T3EVHBlMairNV8pqGp7h1tPjAVVVTmeV8q9y9rnkrl8Oek/p0/ieaeDKXHRHhsr4J1D7OXIksQ1UWb21DYwKzwEgGZb7y+eAkELuvhgrOdrUKwOZA9CpocKnT15xsbFERUdzdEjRzsYJ31dJsrLy8MwIgyl2cmf/vQnAFFbSNDvBILT7ZVzVekllydi88RYOJFfQmRoEJfT2XJSZVERTi9KF/iCSJ2WGrsTu6KikyUaDbI79Pr4tqPU1ViQ5UuzRp19R9tcb83RGnKz87w6ftshL790W+vrSJmQQUiEKNQ3GDGkhWE9XYUpPcrfogwwHfMYvfLKK6SOHc+540d8mlb/woULPPZfv8bhsPv/kVdwxRAITrfCYOkBFe8sy9e+OMgbewr4YN11HfZ1tpxk0GnZW1xGnc1G6AAUc2xhdkQIO2vqsSoKX9XW8PetldwhBWFq0iNX1BM6JoHkeRkDJk8L+UezMQQPfNp6gW+QNBKSQYOzwY4m+EqpOdTRuXb9+vVs2/05B/ccxxQchFNxYusmUs8bVFUlJ6+ck+dOo9W2/4xFNWdB/+Jfi0VECfWA6kWq+wNnLhBlDuLDny8nJKhjpM/69euZN28eK1asYPny5axevZqRI0cyIyGWPx8+SWNzs2+F7wazVsP8yFDqc2u5b2Qc//cvy9h0YhMjVo1l/L1LcTZYO4RcDwgqrbM7gkGJYUQYtrPVV0z6eMmVArT9Nj1852fX8faWF3n5g2e5bvEidBrfXW737fnq0oE6X2LyJIWCQOANwul2EHC5D0t37DtXzL3XTkOr7fyG291yUk51Ld/kF7F09PA+yesNeWX1JIcZGZUYOFE+0cNSKc/LIX7UGH+LIuglkiRhmhBN46FSdAkh6JNC/C1S/9JJyvJQo5l/X/1fAJwrPEHYTZU8fM0C/v3l99iXd4L6+vpeH05VVcaOHcupU64q7sW23qclEAg8x/9ut2KGpQdUVe3RqvzmaA6vbD2ATiNjs/fOgXVERBh59Y1e9XEqCvEpifzHEw+32+7Jk9T5olo+PHGR6SM7TxMfnBKNtXLgi9wFh0dQW16GOsB+PQLfIulkgqfHozoV7KUN/hanX5Ho+OjZdoZjVHI6y+76T+7d8AZzb7yOra/9o08OjFqtlszMTHQ6HYrTSZ3Td7+VmrJGqi42UFlUT0VhHeUFdZTlWygvEAUvr3Q6mUgccITB0gMRwXocikqdteunmPMl1axZPIV7lk4nuBeFB1uYEhvFH/dmU17n2dPXW+e3o5M1OBQ775//mndzvvWo3zt78zlX2cBP541C08U0dfTEEe6CdwNN0rh0Ck8d98uxBb7FMMyM6lRpPFw2dOtNeZEgTpIksr4z2+saYW1xOByUlZXhcDhQAVtTk3tfd0ksPeHCiSq0ehlDkA5TqJ7gcAOhUUYsFU09dxYMaVxOtyJxXECTHGEC4GKNlbHxHZ0Iiytr2XaqlFvn2jEZ++Y0OzMpngmx0fwl+zj1zXZ+eVUmBm3np2hT7jfMjRuDRtKQEprATSOvIa/6NJsLj3R7DLvDSZhey9KMxHbbO8vg63Q6qTlbRP7mve5tkk7LsMVTe6mhZ4RERFJRkEfxudMkjBrbr8cS9D/6xBC0kUaa8y0YhgfO8mNfKTp1Aru1CVtTI1HJntUKa6GlQrPSy5nEl199DRXQ6fREO+2cPHmS+vp6d4qFlt9zreUwoSETkGWtR8bM+NkJ5B+vZORlyegk2f8hrQL/4+9HDmGw9EBieIvB0sTY+I71cjbuOE5imLHPxkoLwTota2dMpqKunlePnsKg0dDQbCc+OIgbx4/iWMlJTjZWMCo0mjRzUru+aRFjKbEdpsnRdTSCTqvB6uh4kews5PpCWTHho5NIbZNPpuzQGfI378VhszNy9RwfaNw5aZOnkntoP4rTidxDFl9B4CMbtTjrm3tVuTxQsVubSMuc1qu+kRHhlJSWIcuyV0aLXq/HqDcQptVyobEBxeHg9ltvwel08l//9V9YrVb+/vc3iYgwkJOzF7t9CpWV26ivt5Kbex673dLt+Fq9ptO7klYnJuOvdALB6VZ8C3sgNtSIRpIorOl8SjQ82MCYBN8/NUaHhnD/lImsyRjPv06bRKnVysmyCt48sJObh1/NlJjxQMeZkVnxk2lstlHb3LnfwNHcSuIvzRq1ZeHChbz++ut88803HDt2jDVr1nSawTd2yhhSl81E1mo49/43NFv7b6o4YfQ4Lp452W/jCwYWw4hwmg6X46wfuGi4/qQ7Q6OnmmO33nwTEqB4uEz2w2tGuMZUnIRFhHPv3DnodFqio6NYtWoVy5cv58Ybb0Sv16HRhHHttav529+2cfKEhtLSeB588GU0Gh3NzeUUFr2FonRd+8kUqqeqeGj7HQm8R/I4Xrb/EAZLD2hkiYhgHRerO3eILSyvYfb4YVTU9N7rvyckSeKm0cP56sJFVoQXUFR00L2v02R0haUU1JVSZWuVad/pMj49VIjVoTCrE0fbrkKuu2L4ilnETBtF7tv/pGT/qR516E2YpTEkBLvtyi2qN9TQBOsIyozFllPr97XwvmKpKEPppJBoCz3VHPv1b37LqFGjARVJ6voyrNFo0Gq17Lyow6TXsfa73+X4f/2Ee+65ntjwYB68//sUZG+joKCAG25YRFpaAkuXrujy96zXx2AyDUOWu54RtlQ2YbxicugIPCUQnG7FkpAHxJuN5FR0/sTx77fM55XPD3LkQjX/e9+SPjnTdUdsSDD/Ni0DVZ3EgYN/IjnZNRXdVW2jiZFpfFm4D42kRSkzMzwhhRVjuy6S1pt0/2FpCYT9MKGdj4uvUZyibMBQwzgqnMYDZQRNiUUapLWo6quqSE6f2OX+nmqOmc1m9h/Yz8zrVlJwdD84VZzOZux216xNy9KZoihIksS4ceOg2oKj4AzGrP8kdPRkpH99lKbaMuounqVq3/tYE6LR2Otpyt+Kckzl5cdvJOj1l5D1rqXs7353Pk1NF4iKvLpb3RJHhVNfbSXIrPfBJyUYKkhd5PwZSITB4gGpUcHkVHQ+g2LQaSmpbuB8eSPvfnOMm+dM6DIPiy+QJInUYYs5n/M5I0cs6bK2kSTJfHfkNQCUN+9AbawEFvaLTLYm78KxvUGWNUPK70EAcpAO06Romo5XEJQR429xeoW1oQ5jcNf5ZTypOSaplfz10amEhH6PoOAEKi0fctXVG9j457cYd9VMEpVGYqdmYK2uI//Nzwhb+whNjRXoRk8GQGcMwpw2heQ5t1BTNIXar38PhlhMqdcSlHkfjj/Pxv7DKRj0odTWZgMqUVFzcToUmq0OjMG6Dr8rh91J0Zlqxs9u75QvEAQCwmDxgLToIHblVHa5//+7bT7Pf7SL13fmcMNV45AkOvX/8BUxMaO5WLwP8GxmJGbcPCxFpyk89D6Jk1f7PJNs2yq1viYoLJwmSy1BYeH9dgzBwCMbNBiGh2E9U41xTIS/xfEarc7Auf17kDUyaZOndvhNefK7DA0bzuxrnwWgvraQ0Lo4Tux9GVuohYbSCsInDyfvw+00FxWTeMNCQofFUrpvDw2FFwhOTmm37OS01lEvm8nNywNAZ4yjcdJygoNcBmFTUykNxVOo1VdSV2VFb9SSODqc4PD2S0MarYzOIG4Lgo5ISMLpdjCQFB5EdWMz9i4SNMmyTFxYEMOjTDz2zrf8btOufpfJWwcoc9JYYscs4sLet1D6mKuhLRd3HUMX1rEMweX05ITYFZFJyVQWXei1fILARROqRw7W4aho8vtUs7cMm5jBqOlXkTIhg7zsgz136IGQsGTikrNIn3kP9c7xSJYadJER1H6xjZH33UToMNdybtz0mZQdPgq0d5QvbtLz8HvH3Q9KkqxFEz0RWWOirDCX7M9CiBkWyrAJUUyYm0RkUjAXz9Vw4WQVF05WUV3iWvJubnLg7CSKUCAIAJ9bMcPiCZHBelQVLE12okI6d1a7feEUFmbW8afN+4kN7fkG3ne8v6jog8NJyryJggNvMGzmXT6ZabHXNLYLe+6KnpwQu0JnMOIYwBpLgoFFnxSCLa+W5gt1mCbHDLp8Hzq9ASRwOhxousiZ5A21ebk4jh6hSlIoqKsn8Qe3otG3cYCVJILjE6g9c7LHZSdVsVNTXkZxXi7X3dN+OTgyIZiIuCD3mBdOVhERH0xJjoVR07v2dRNcubgS8wsfloCn5Rr6z3MVmE1de887FZW0pDiuTtZz7ty5fpNHVVXMZgOVlTt61d+QGE3TmTI0ci8Nq0tPwwXHj9Dc6FlYc09OiF1hr6tGvbAPgqt7J2t/UB4CY2b5W4ohgyEtDJtai9JoRxMy+Bw9U8ZP4sKJo6RlTOnTOIrDwdkP3+eBx3+GPT+f3C9PkDp9XId2sdOmcO6jTxk5Ykz3y066YAq++ogpt/+kwxiSJLVzeJbc2+ky+7XgykaS/L8kJAwWD5AvOaZljYwmJrSHBHHj4wZAIoDRve8a5RsJhg/PIu+wZ9PhnjghdkbhN++TcNUyiE3tq7i+o+hLf0sw5FAVFUk3OBME6oxGmuosfXYOP73xTSZ8/4doDAYOf36WhKld/8aHXTOX/C++Iu26JV22Kc8fxvilniW2a6htpuhMNTVlTQyb4LXogisEYbAMAlquQf6eDgs0dHoDOp1nT8S9CZsGSFv6Q3I/+wsjbvhRr2QUDA4MaWFYz1RhGu8ja3qAiRmWRl1FOeaY3i2n2JqtNDU3YoqO4vTbXxM7MYWErK4tB705jKCIUGrPnyesk3xJRbsOED9+GMaozoubXs6YGXGoqkr8yKFTOkHgWwJhsVYYLB7gfmgS9koHdEYTedkH3B+NJMt9nhpvi6TRIInU/EMeSSPBIC6OGB6XQPHZU14bLDuzP2fXp+8SExdDxiRXqQsVieT5GT32jb1qFuc+/ITQ1DTky1IpOCxVBGd5XjZAI1LvC3rAlTjOv79R8S31gJaInMF7Oe0/ksalk5Y5jeGX/tReFnPrjv4YUxCAyNKgrehsqSgnNMq7nDJ7DmylrDCXn/3i9wwPjiRz1vVeHzd10TzyP++4RCkifQS+xlWt2b8yCIPFEy7NsCj+PlsBjqO5Gbut68KLvcXZTQp0wdDBMCIc69kAcq72gooLeYRGx3hUgkJVVb7Y/i6qVmb1ivvZv+lPTF19X2sHLzKK6kLDCImLpOZ0a3mM8uzDRI4c1hd1BIIOSJLk94d2YbB4wqWzJItsq90iyRIGU7DPx02cvpBzH/6Rs+8/i9PWf8UWBf5FNmjQhOqxl/Vf5uT+wN5so7mxEWt9XY9tG5rqeOXN/yJt9CS+t+pefrX+QUJTRxIc5PIdyczM5I8fv4WjynPDLWbqdCpPn0dptuOos5C/6wghI0b3qn5XV/j7RiUIEITTbeDTMrMi7JXu0Wh1KIrvZ0OCk8cxKnkcTmsjZz94gXG3/YfPjyEIDPSJITRml6GNNg2anCw6vYGIhCSKTp/otiBifX0tH3z6JxYvuo1hCaMAqCk8z4TZz7RrJ2k1OJpseFN+MG3xNZx85wP0oSFMvfsWZL1vL+2D40wI+pNA+A4Ig8UDFDHD4jGOfqyu7HQ0d3tDEAwNdMmhNBdYMKQNnoiVpHHpgMvfqjDvDCfOHSA+KoXIiFjs9maarPV8tOVlbvvug+g0LlPEYbMSmpTWYSxZK+OwepcsURMURPyUCZhHjkI29JB6QSDoDYPN6fbFF18kIyMDs9mM2WwmKyuLzZs3u/fX19fzwAMPkJycjMlkYvz48bz44os9jvv++++Tnp6OwWAgPT2dTZs2ea9JP+KeYfGzHIFOf6dXrzj8NbEZc/r1GAL/o4s2oTQ6BpUD7r6Sffw95+84NAoOs5Zmu5Xd2Z/z6Rev0djUwIXi86xacZ/bWAFwOu1Exw/vMJbRbKImv8prGaImTkRnGogs24IrkUFXSyg5OZnf/va37N+/n/3797Nw4UJWrVrF8ePHAVi3bh1btmzhjTfe4OTJk6xbt46f/OQnfPTRR12OuWvXLm699VbuvPNODh8+zJ133sktt9zCnj17+qZZPyAqBndPybkzhMXF98vY1spimi1VRGfM75fxBYGFYYSrMGKgY1fs/CPvH6SEprB8xHKGJQxDbzWSOX4Oy6+5g3kzV1NaUs6Y4ZMJMYa6+ymKgixJndbXMoSHYLnYd917W79LIOgMV1izf/HKYFm5ciXLly9nzJgxjBkzhieeeIKQkBB2794NuIyPNWvWsGDBAtLS0rj//vuZPHky+/fv73LM5557jiVLlrB+/XrGjRvH+vXrWbRoUQdnsUBgsBVoG2jiRo7CUlHeP4M3N6APH6gswoIWfOm46Q2yUTtgeVlUVWVfyT62X9iOXfHuhv5F/hcsTFlIfLDLUF+4cCHPPPMMP/nJTzh27Bhr1qxBo9Hwpz/9qd1nlnNkB2ajrsv6WsFx4dSdL+yTXr2t3yUQdIW/74G9jhJyOp1s3LiRhoYGsrKyALj66qv5+OOPKSoqQlVVvv76a86cOcPSpUu7HGfXrl1ce+217bYtXbqUnTt3dnt8m82GxWJp99dfiLxxniHLGoLDw8k5tI/c7APkHTnUp/FURSHv7y9x4fPXKD/2LWGp430kqWAwoDYPjL/SVwVfMSp8FFmJWWzJ3dJje7vTTnZZNtsvbCfKGNVumWf9+vUYDAZeeuklli9fzurVqxnZSSbawqO7WX37D9zVltsaNwBRE1KpyS3tk15tqzlfPr5A4C2BsL7gtdPt0aNHycrKwmq1EhISwqZNm0hPdzmcvfDCC9x3330kJyej1WqRZZmXXnqJq6++usvxSkpKiItr/+QcFxdHSUlJt3I8+eSTPPbYY96K3yvEUpDnJIwaC4DidLL7g3cIMoeh0WoJi0tAq/Mm7gHyP/0j0VMWowmKoLH4HMGJHS/8gqGLxmzAWd/crwURmxxNNCvNRBgjAAgzdO/oe7H+IvtL9zMvaR4h+hC0cvtLqNlsJiYmhrVr17J27VrAVYIiMzPT3Wbba08y9uoVTF2V2mV9LUOIAVtj35Zvelu/SyDojEBYEvLaYBk7dizZ2dnU1NTw/vvvs2bNGrZv3056ejovvPACu3fv5uOPPyY1NZUdO3bw4x//mISEBBYvXtzlmJcbBJ4UEVu/fj0PPvig+73FYiElJcVbdTzCPcPi77M1iJA1GmZ/93bqqipw2h2c3rmDkdOuwhgS4vEYqsFMcFQ8UlA4piixHHSloR9upulwOUGZvavP4wlf5H/B4tTWa1OkMZK9xXuZmTCzXbvTVafZXbybmfEzWTFiBbLU+xRWkqKSMGISQJf1tfK/PEx8Rt8Kfva2fpdA0BmB4HTrtcGi1+sZNcqVQ2D69Ons27eP559/nueee46HHnqITZs2cf31rhTTGRkZZGdn87vf/a5LgyU+Pr7DbEpZWVmHWZfLMRgMGAYofE8UP+w9oZGu4mt6k4nKwgJ3+GdXNFpqsVtdyeEcqpYDb/8vk+/4OTqjqd9l9RgVCncU0lzWRFBaKPHT4yk/VQWXljBiMrxL0R7I+NNxU5Ik0EioTgVJ49scl6qqcrLqJPHB8Zi0rd+tidET2Zy7uUP7sZFjqWyq5HjlcY6UHyE5NJk5SZ1HrMmyTF1zExtzd5NjKcKpqlQ11rk/R6M5okf5rOXVhCya3EvtBALfEwgzLH2+Cqiqis1mw263Y7fbkeX2Q2o0GpRuasFkZWXx+eeft9u2detWZs+e3VfRfIYofth3gsyuqfYzu7+ltqzr5b687AM4HQ6cDidRGfMZvugWpJMfD/j0VrOlFmtZCRf/uYtjr26k2VJPY3Extuoqis/Y0Zn1jLh5NNYKKzkfnEVqdqIxuOz//H/kDais/Ym/HTdN4yJpPFyOo7KJplNVqHbf1Mj5NOdTTFoTM+JndNgXpg+jpMH1HS2uL8ahOACYnTSbm8fczK3jbsXqtLKjcAelDR39TCKio9h05GvOW4q4dcR8fjbiWooKCthWcozTZw7gqK/vWcA+zOAIBEMVr2ZYHnroIZYtW0ZKSgp1dXVs3LiRbdu2sWXLFsxmM/Pnz+eXv/wlJpOJ1NRUtm/fzmuvvcYzz7RmcrzrrrtISkriySefBOBnP/sZ8+bN46mnnmLVqlV89NFHfPHFF3z77be+1bQPSAHhbjT4aZldObt3J+aYuE6X/UyhZiITk9tvjI+HM1sgJA6Spva7nM31DZz77AuCosKIz5xI3NRMSnb9E0lnxNHUiPnqYURNcC1TpC5NxWlzojW2/pRycmpx2J1odYPfwXHhwoVs2LCBlStXEhERwSOPPDKgjpuSTkNQZizNF+owjomgMbuMoIwYJG3vb+gnK08yMXoiw8M65kABmJU4i825mwnSBmHSmdhfup/rR1zfbhloQfIC6u317C3ZywzNDMKN4e59mbNn8sFb7zDvX2Jpyi9hzSOPYNIZCbJp2HUgmx/c9cuehVRF8UJBYCEFQPVDrwyW0tJS7rzzToqLiwkLCyMjI4MtW7awZMkSADZu3Mj69eu54447qKqqIjU1lSeeeIIf/ehH7jEKCgrazcLMnj2bjRs38vDDD/PII48wcuRI3nnnHa666iofqSgINIZNnEz+4YOkZU7rsK/TsDmjGYbPgwt7+122/K2fo9VpGH/jciRD61JB0sLOlzQlSWpnrAAkXZPCha35DL9+RL/KOhAEguOmJEsYUs0ABE2OxXqyEtPEaI/6/rPonzgUByH6EKbFub5v+ZZ8rht+XZd9ZEnm+hGtlZNPV52moqmC2KBWXxqNrCHMEMbiYYs5VHYIySIxJXYKAGNvX0hmzvkOn1m8TccPbrvHI7kHU9I8wZWC/4sfemWwvPzyy93uj4+P55VXXum2zbZt2zpsu/nmm7n55pu9EUUwiDEEBeN0Ojrd5+zKP0JjgGYPptL7iCRJJF2zsE9jGMIMhI2OIOfDc+jCDCRkJXQwagYLgea4KWkkZLMeR2UT2qjO/ZpUVWVvyV6aHE1Mip5ElCmKbRe2AVBtrSYmyDsfI1mSsTk7LzkhSRJT46ay8+JOtl/YTrldwWiO5euPW8Oja2otpIZFYjAFdXscxalwftM/cdqd6MN8X0RUIOgLkuT3CRZRS8gb/G1dDiWcjvYGi91m5czuf5I8fkLnHTSXvqqq6nEVyrS0tHbhpeBKerZ69ep+T3wWOSaCyDER2OuaKdpWiKPRTsq1qej7MUT3SsEwzEzT8UrkEB2yof0lzKE42Jq3ldmJs9st0ySHJHOq6hRFdUUsHOadQToibAT7S/eTW5vL3KS5nS5lzk50+dwpqsrmilr3dmdzM3s2vM6SB36E3MNSWvYr2xi/ejqmaLNX8gkEA4GE/wNPhMHiCcKFxecEmcM4u2cnxtBQLOVlBJnDGD93AbLczUXdnAR1JWBOGDhB+4guVE/qdWk4HQp5H51j+HdGdXBMF3iPcXwk+buOU5DqqrmTFJJETFAMOwp3cG3qteg17Q3DURGjyC7LZkzEGK/zKmlkDVclXMWximPk1OYwMrzrfEDVdic19taEd012BxHp42lqrMVSXkRdZQkN1WU0N9S1+sZJrlkhi9PAV8c0KE6VsWOGMSZl8C8pCgS+RBgsAr+QPH4iADUlxSSPn+jZTaTy3IA43fYHGq1MwvwUcj44R9iIcCx5taQuH4HWOPgdc/2BJEuUq1XuGY+cmhzOVJ3h+uHXd/ldyozN7NMxx0aMZVvhNurt9WgkDZZmSwefq801WuJ1Kv975qzraVRRmVR7htM7LxIcGUtodAKJY6cSFBLRpeGqqiqHTpzkk6++RpYlZk2dTJQHodACQX8iloQGGf4+WUOR8HgvZksGeahnULSJ4TeMxFJYR9r1w8n7LAeNQYMxPpj4aSIxnrfoQ40c3PktTqeTmfMWMIL+nZHQaXQsSV1CcX0xQbogQnQhaC6bEZyT1EnHcd6laJAkiakT0pk6IZ1mu51vDxykobGRoCAjV0+bhkEnlhUFA8+gTBwnEPiN5BlwMRsSMz1qHojVajV6DREjwgEYeeNoAPK35vtRosHL5MmubLTHjxykuLiQhITkHnr4hoSQgVuS1Ot0LJzlipissVj4cudunE6FhPgopnk6MykQ+IBASBwnDBYPEJeEACF8GJSd9Li5v5OeCQaG9ElT2Lv96wEzWPxFuNnM8vnzADh/oYBPv94GwMRxoxie2D9lSQSCFgLhPigMFsHgQXF4tSzk76RnnlJTVI/ziwIkWUJGBY2MrHX9RY+PxGAWSwDdIUkSsvbKupSNTBnGyJRhKIrC/mPHOH7qPBqtzOypUwgLCfW3eIIhSqd5sgaQK+tX3kf8HdJ1xaPRuYyWM1shZQaYundEDISkZ55giwli4vxkVFVFUVRUh4ricKLaFS7susiopWn+FlEQoMiyzMyMDACszTa+3X+AJquN0NBgrp4yFa2PDDmnU1z7rnQCYflRGCyCwcW45S7v55yvITQBYsd32TTQkp51hSSDRnf5zJHOL7IMRuzNzchDoAxCXzHqDSy+VIOtrLqSv/z9bZYNX0Z4bBDhcd0nresJWfb/zUrgf/ztdDu4wy4GiECwLAVtkCQYuRDKT/v/FyTwK4qicHTfPsJjPUvVfyWgqAoHavZy53XfIW1SNKqqkne0gryjFdgae+d0Li6BApfTrX+vt8Jg8QJxbwwwEqdA2Ql/S9G/+OBOkZaWxnPPPdduW2ZmZr9n+x0Ics+eJiIhhpHDx/pblIDA5rSxOXczC1IWEKIPASAiPpi0SdEMmxBF5cUG8o5UUHSmGsUpCiwKPCcQigALg0UweHHYQB7iq5oDZCQPVqMmJW0EVRXl/hYjIKhoqmDbhW1cl3YdJm3HOkuyLJE4Kpy0jGhiUkK5cKqavCMVVF7s/xpdgqGBvx/ah/jVXjBkuZgNhftg5n3+lkTgR3IuniUpWoT0nqs+R1lTGUvTlnrUXm/SkjohCoDa8ibyjlQAEDfCjEnUuxJ0gsjDMkhomQjz98kStKGhol+MFW/O8UAUV1QVBaXZVZumdXWozdTs5bO0UudvVFVFVdpr16sQRVVFVZygOEFRwOkAxYnqvLTN6XC9dra8doDT2W6b672rn9JoR9KpoCpIqhNUpfWv7XKYpAFZBknr8lJu+X86l/g7A8+ReiDZX7KfIF2QuwCjt4TFmAiLMaEqKqV5FkpzLGj1MgmjwtFoxSS8wIWECGsWCAIK/6/Stkcyasn9poiqsiLyTm5j4oyr0OhaKld319O1U1XAabVRtSuXuswL7l22mkaqzu+m+MjfAXDam7BcPOF+D2C3WqgrPeveJl38kkjjXJehIMsgyaiyFkmWXUtzsgwaLZKsAY3GVWFbo0HSaBm9cCk/uecHrP2X+y5t0zD1miWsuv56Hn34IVd7SQPypf8txoqKax5adbpC2tUWY8kJqhOndQ9qUw2SKdx3H/ogwtJswa7YSY9K7/NYkiwRPyIMALvNSdHpahSnSnC4QTysCcQMi0DQawLNsugnRl3jWu4YyTAyGjLJ/mIPV103z6sxYmJiqQ1tJuOH81i7di133303+WWF6ENnsOyuh1i9ejU6QzChCeNJyFje2lFjIjRutHtbpXQW/aTVvVNEq0UTEY0mMbXN+FokowkpJMyDATRAx6UKKXoEjQ2lBF+hBkt2WTazEmb5fFydQcOwS0tGdVVWFJGH5YonEKJlhcEiEAwSDMEmnB7WQkpLS+OBH/2Y72Zew1XjJ/Pe3z+ioqKC9957j+3bt7sy/raZ3h2sZQzspUcwjVvlbzH8QqO9Ea2kRa/pX5+T0EgjoZHGfj2GYJAg8rAEPu7ZaX+7SAsCCn8UV4welkTRmTyP2lafKCBxQQZPvfS/zJs3D4fDwYEDB1i9ejUjR45s13bhwoW8/vrrfPPNNxw7dow1a9Z0LGMQYN//Y7ueI37sDchDPVKsC3YX7+aqhKv8LYZAMGAIg0Ug6CW+mpVomWj1JLS4tqyCqOT4HsdUHU60oUZ0RoM7469Op2PBggWsWbOG7OxsfvGvd3DixAl2797N+vXrmTdvHitWrGDq1KmoqtrBqOnLMlx/GHcqKnGJ0/o0hq8Y6LDwKmsV4YZwNLLI8Cu4crgyH00Egi5oavS8rT+KK6pOJ1VF5SSO7j6U12mz41RVFKeCrJFxNDe5+rczGlpfty1joNfrsVqtZGdnu/dnZmZybVY8//3i2l7J3R9LTpJ65SY+O1R6iIXDFvpbDIFgQBEzLB7QkuEvwGbEBf1AkFnL2ffe96ht21mJ5cuXd7rU4mumXT+Xk/880GM7yaClzt7I8a8Pcnz7IWoLj6KRJapKCyg+8hnFRz6jsrEIu93O9u3bO8wO/POf//Tp7IBHS07eIl2ZswuFdYUkhiQGhBOkQDCQCINFIGhDyjULMIR7ErXSOitRW1tLQUGBe6nFmxv9p/97mGETozxuf3bvKSYtmNnjEkRwkAltqIlJi6czInMMh/ccwO5wcup8IedqzVTKqTzy31uQJLBarfz85z9vN159fT2PP/64z4wWXxt3dqvFFTbtIUeK8zlSnNfr4wUSp6tOMz6q66KfAsFQRSwJCQR+JH6EmdhhZsAzP4/q0lLGZk3ocdzpU6bw1ttvs/o73yEiIoLfv7sVg0FPXFwYK1asICwsjMcff5zPPvsEu93pO4W6wNeVs3OOvM6Iyd33dzgVtuWc5XDpMSJMoVysq6DIUsWysVN7fdyuGCgH7DPVZxgZ3r+zeAJBoCIMFoHAT6iqSrO11Vjoyc+jobYeVVE8Wgr4/q23YEdqZ5zk5uayePFs7rvvOsaOvQGA3/33Exw7cRZUldLC4+zb8S6OSzdaVVUoLzrIib0vU28pp6HW85mg/sbusBJkCO1036GiXL7M3Y/dqbJ41ATWzfkOsuSaTP7i/EEe3PxHHl90N8F634XqDlRYeIGlgMWpi30+rkAwGBAGiweIpWJBfyBJEnpjqx9GT068J785yPQVniWNCw4O6jCj8atf/Yrk5DE4FT1n8rIZk5bJxWJX4UAVUDSR/ObZt5FkGVVRAImYpKkkj/suF0t+gk4K7rPOvkLtJGSp2eGguL6SL3MO8Yu53+203+KRU5meNIanv30XsyEEi62eKfFjWDgik1Bj7w2YgXDAPlx+mEnRk3w6pkAwmBAGi0AQIKxfv56cnJwOsyIt2Jqa0BsMgAdLEJ14iDucCntPFxI+YS6S7gLDEtOJjIigqroGVVX5v//7P37xo3V8++23VFRUoKoqZWVlvnGQ9SFORzN1zbXu93879k+K6yqRJBWrw87Pr76p2/7hxhAeXXiXq76SqvLczg8J0htZMiqz1zL1dO76iqqqVDRWMDlmss/GFAgGG8JgEQgChO78POqrLRhMJvf2npYgJEnmeF4J+84WodNokCRwOJ3MGJPED5ZMw9Y8nk37vnYvlQAsW7aMSK2BpJh4Kipc1XvffPNNXnjhhYDKeltTk0Ow1vVZNNjsXKyr4KdZ3me7lSQJRVFxqkqfjBXwvY/O5VidVsIMnjmDCwRDFREl5AUirFngL3IOnWLkjInu992FCddWVVHl0HAsr5QfLJnGHQszuf2aTIx6ndv/xaAPYkracOw4CQpy3fzffvtt1v32/3Hs9HH3cX7yk5+6o5/Wfv+GDtFJaWlpJCUltYsm6iphmq+Sq0VEjADFSWOzlae+2cj3M+d71b8FRVH4zY63iDKZe9V/ILE5bBi1Ij2+4MpGzLB4gHLJUhG+LAJ/MWHuVLa/9Rlzb7senV7b7RLEuZx8nt7fyDe/ar98cPky0tikMSDJzMpaxLfffE5zsw2bw4lOI+NERZZlzucU8NdX3kECxlaew2ltxHL6MGVfbgJAsTaiOBw05Jx0b3PU19KQc5LSLze18zRxWhupO3OEsi8/uLRFcrct+/IDVFpzHgEuB2NZcre9tBWAhmNNvKL9B/8x77t9cp7Vyjomxo7odf+BospaRZAuyN9iCAR+RRgsHuBUXBdJjSwsFoF/0Oi0ZN24iF1/20pQeCjjr57S6RKE1Wbn5Q++5g93dqwx09kyUklRMXfdcSdffvEJddVN7DuZy8LZ6e36OZwKBYUlvP16NXaHxLmcKrbtKsJWb0HSm5A1Dv7y8T9ImprF2rVr0YY8RvCI8Sz9+WOsXr3aPYOiMa4jdEwGsYtudI/d0rbttp7IuWjBqpnGv81O7blxN8iyzPr5t/LkjrcYH5dEqMHUcyc/cKb6DBVNFcxOnO1vUQQCvyKWhDygZYZFGCwCf2IKDWHe7cupr6ymqbah0zavfLSdu78zn4wRCR329ZRtNjTC1MFYAdBqZEakJjJqWgbGEBNTl13DLQ8/wNTly2iqa8De3Orsm5aWRnl5ebv+vqypU1LVxJG9JVwzf5hPxgNYl3Uzf9jzoc/G8yW7i3ejqqowVgQCvDRYXnzxRTIyMjCbzZjNZrKysti8ebN7vyRJnf49/fTTXY65YcOGTvtYrdbea+VjnJdKlshiTUjgZ458vZdxs6cTnRLXYd/RsxeYNiYZk9HQaV9fZJttu6w0Yd4UdHpdB+cup7PzRHR9Ta5mabSz46t8brhhtE/T0ht1euov1VoKFByKg3/k/YMRYSMYGznW3+IIBAGBV0tCycnJ/Pa3v2XUqFEAvPrqq6xatYpDhw4xYcKEdtPNAJs3b+aee+7hppu6DzM0m82cPn263TZjH3Ii+BqxJCQIBOqqaqmvspBxTWKn+4+dKeB7y7t+Er88kiUtLY21a9eydu1a97bMzMx2yziXc/myUnRsLMdPHCc42JWjRVVVqqqqPOrrTXI1q93BZ5+d47urxiD3w+8wPjgau9OJLkDCt78q+IoFKQswaDo3PgWCKxGvDJaVK1e2e//EE0/w4osvsnv3biZMmEB8fPuy9x999BHXXHMNI0Z079QmSVKHvoFEy1OhRsywCPxI9j92MufWpV03kNR+L4h3eYK0JlsTiuLE0ezg3MGzlJeXu2W4fPakt8nVFEVl08fnWLV8JFp9/xgUWanj2ZZzgiWj/Z+Yze60E6IPEcaKQHAZvXa6dTqdvPfeezQ0NJCVldVhf2lpKZ999hmvvvpqj2PV19eTmpqK0+kkMzOTxx9/nClTpnTbx2azYbPZ3O8tFov3SniI85LBIguPH4GfOL7jIPGjhiF38SV0OJztImwu53RVA3su1vC98QnoNa1jNCsKqtpq6FQ22dlzsYZXjxdR02in7ZCS0jFB2kMPPcS//+KX1Dc2sOHdVwkKCkJvNGCz2dyzJy2GS2+Sq6mqyt8+PcvSBakEBes9+qx6Q1ldPcnhEf02vqfYFTv/yP8HS1KX+FsUgSDg8NpgOXr0KFlZWVitVkJCQti0aRPp6R0d9V599VVCQ0O58cbuvf/HjRvHhg0bmDRpEhaLheeff545c+Zw+PBhRo8e3WW/J598kscee8xb8XuFWBIS+JNj2/dhDAlh1LTOK/QWFJXy7KY9PHrXNZ3uz7dY+eBUCXdMTOR/9uSi18poZAlLs4N9F2t5bn8+jXYns5LCcaoq0+LMLEiKJDW8fdTM2/sqMZvN7Nmzh8cee8y9lLR0WCYz7liO1d5MuCmM6dNmcOrUKTQaTTvDpTfJ1T7emsPsqfFERvVvBE+hpYxZKV1fb/qT4vpijlQcIVgXjENxsDR1KTqNzi+yCARdEQh3P68NlrFjx5KdnU1NTQ3vv/8+a9asYfv27R2Mlr/+9a/ccccdPfqizJo1i1mzZrnfz5kzh6lTp/L73/+eF154oct+69ev58EHH3S/t1gspKSkeKuOR7RECQmnW8FAU1teQ5OlkYnzZ3TZxmQysjg9gTBzx2KAdc0O/nKwgMfmjkKjkVk/u9XJ9gWjntlJ4aybkcYFSxMljc2YNa6ooMuNle4YvnwW8QkJ2OqbKCi5QO6nuQSFhGAymfjwww/dyz49+cdczj+25zNuRATJyf2f2K24vtxvYc1HKo5wbeq1/b6cJxAMdrxe5NDr9YwaNYrp06fz5JNPMnnyZJ5//vl2bb755htOnz7Nvffe671AssyMGTM4e/Zst+0MBoM7Wqnlr79QRJSQwE8c/mIX066f222b47ml7Dp1AafT0WHfc/vyeWj2SDSajj/1tk6wKWYTY4MkCvLzeiWnVq/jjrvv4tTuw0yZOpP6+npqG63853/+p9eRSAA79hQSG2Fk7OjIXsnjLdFBkX5LDGnQGISxIhB4QJ8Tx6mq2s6XBODll19m2rRpTJ7sfaEuVVXJzs5m0iT/O7+10BKIKa4pgoGkpqwcU4ixS7+VFhZMG0PGqET+sukb5k5KY8LY4QD88UA+142IJqgLR1VvnWAtdQc4sTcbe3M9Jfm7ObH3Zfc+a2MV5UUHqW0y81+/f5m7Vi9i5qI7mbNglXvZ58MPP/RI771HStEgMSWjY+h2f5FsjuEPez5hctxo5o+YMGDHBdDKIn+nYHDg7+o0Xv1SHnroIZYtW0ZKSgp1dXVs3LiRbdu2sWXLFncbi8XCe++9x//8z/90OsZdd91FUlISTz75JACPPfYYs2bNYvTo0VgsFl544QWys7P5wx/+0Ae1+gdhrwgGkpDICOoqa3A6HWg03f9UI8NC+JebFrDpi30cOV/ECRuszJrEjPiuC+Z56wQbP2IC6WlzMBifIG7YVaTPvMe9T6N7hpikqRhN8Vw8txWT0cDVk+P4bNcFppQ2MG9mkkc6Hz9bSV2VlUUL+pbF1ltuGD8DmMFzOz8ccIPl8tw0AkGg4u97oFcGS2lpKXfeeSfFxcWEhYWRkZHBli1bWLKk1aN948aNqKrKbbfd1ukYBQUF7Z4Ya2pquP/++ykpKSEsLIwpU6awY8cOZs6c2UuVfI+4oAj8gVarZfqKhWx77RNm3rCE4IigbmdbJEnixiUzUVWVDbv3MbMbYwV6X2G4u3wq46bezgXNt8iyjEGv4d9unsAH23L547vHqK3rPjlbbmEteTk1XL/U+yUkX+FQHNRZrYQOQB6owrpCjlYcZWS4//QVCAYTXhksL7/8co9t7r//fu6///4u92/btq3d+2effZZnn33WGzEGnNYlIX/blwI3xgg490X/jG0I6Z9xe4E5OowF31/J0W17qS4uZ/73VyDL3eciqXcqWFSJ13ftZWbaMMYm+CbHkdPhKgfQ41KSJBEdHU1xcTFarcwti0disVhYd1cBTdaOfjYApRWNHDpYyo03jPGJrL3ltoyr+eTkQW6f0r+p8HcX78aoMbJs+LJ+PY5AMJQQi6eCwUnytP4b21bZf2NfhrXeTk1ZIxZ7LcgqWlmLTqtFq9Wi07j+azUaJi/KorygjBPfZDNxfve6h2o1/Gz2DJyKwkeHj1JYU0tqTDSjoqP6JKtG44qiWb9+PS+88AJLliwhNjbWvZT0pz/9CYCrb1zCvAXzeP3119sZNbKs6TRLraWuma+3F3DLd/xrrAAkmeM5Wv4Z0D8Gy+mq01Q0VeBUncxKmNVzB4FA4EYYLJ5waYpFzK9cGTTWNVNRWIequLKsqi1/qoqi0PreizG7+u4kjA5HkmBP4V6Gm0fgdDpxOJ04HE6cioLT4XDlAVJcJXvs9Xnkf3kCxe5A1rbOaqgSoLafBVRR0QNnK5s4ERKCNKrrjNNqpzJKtGgpIRFkOw/MxWw2ExMT0y6t/5o1a8jMzARc0XTrfr6OwoLCdv4xR4+fob6hffZbq9XOp5vPc8uNY3t0Lu5vduSe4MDFkywc7p0xrKoqu4t341SdTIubhklror65niMVR2i0N6KioqgKQdogEkMSmZM0p580EAiGNsJg8QKxInRlkDoxCsXpyv4qyxKSDJIsIckSstTmvQ+/EInN0UxP8iQyrvsQ5/5k88lDHrWTgNlXzebBdQ+285F54smnKSpvrTLtcDjZ9PE5vrN6NFpt742V3tRE6oz9F0/w4JybvTr2rou7sCt20qPSCTOEcbD0IDanDa2sZVrcNJFeXyDwIcJg8QDvnqUFgx1TSP+lgB8IfHUDvxxJ8tCo6CIjdJBRS73NgaIoSEh88OFZli0fgUkfGJchg8YzR1urw8pXBV8Rog9hZPhIkkJaI6CuSriqv8QTCK54AuNKEeC0BAkJp1vBlUxpXT4H8z9Ap9HjUG0UVRRwLO8ASBqQZOob6ymvLaeoohybQyGvvIyTF46hqgqqqmBtbiLYVMdH/9iK3BzJ1ddMIDwkcGYgPHkwKWssY0/xHpYPX46mB+dngWAoEQiP7cJgEQgEHrFq0i9pbK7DrtiQgoOoqKzHaExARaHeUkvRhSJkWcPUEeOprLdT21iLQadDkjTIkoxG1jA8MQZzPATpq0iMCva3Sl5zpPwI14+4HtnT2SaBYCjh52d2YbB4QCBYlgKBvwk3RpA5bgpr165l8lWz2Pzhx9x9+53ce++9yLKMRiNT21DLP7J3EBkMGcNGMSJ+bOsAqoQ5KAxJVpkyyndROLIsd8iV1FIh2hucirPLfVaHle2F24kNihXGikDgJ8QvzwNUVTjcCgYPvrqBd8eqe+5g1pzZrFixgtzcXMaOHUtMYgJJ0cNYt/IehqekdZlcbsaYuWw/ttVnsnSXyM4bujJEDpQe4EDpARYOW8iU2Cm9llMgEPQNMcMiEAwxfHUD74xGu41/5p8gbbyJDa+/RrgphMzMTDIzM7nn4Z+wcvoioPvkcqGmEJqbK3wiT0/H8obLw6prrDXsK93HqPBRDA8b7itxBQJBLxEGiweoqP5euhMIPMZXN/DOcChO5qSms3bpv3Tb7q233iI+Pr5dHpYtW7awbds2FMXBxOKvOPxVJJMX3tpnmbytidQVElDfXM/OizuJC46juL6YhcMWotcM7qgxgWCoIAwWDxERQoLBgq9u4C2oqkqzqqKqDiRJorHZQW2THYNWxqjTdLrcJEkSa9asaRda/eyzz7JgwQJQFaKHz+Xi6bxey9SW3tZEupw6Wz3vHd3NLRlzaHY2MznG+2rzAoGg/xAGiweI2oeCwYSvbuAtfFF8nD1lp4gLisIcHcOOk+eJPVfK2Yp61KZGzp7PYc/FGuwWDSu7GMNacQTVYQVAlrSoKISEx/Rapv7gP+Z9j22nywjWBROsG3wRTALBUEcYLB7QedpygcB31Nhq/C1Cl9hVDatTp7NiygJGjRrF4S0f8v/uvp1ZMRHMmXMNKE6uSgxnyghdu36qqmA5/EdUWy3ayLGoig3bxV1Ysl+gqlohZJiYwRAIBJ4jDBaBIAAw683+FqFLQvVhnKhxLSktXryYqKgo93JTWFgYJpPJ3bbh/Ic4a3PBUUdT/hcEDX8RrTkVAKf0CIbELMxT13L6768wI70fC1gKBAKfcnnkoT8QYc2eoKoirFnQrwRybo+5MYkUNlSjqCpGo5F33nmH2tpaCgoKiIyM5Ec/+hGPPvoow4qOo9QXY566jrikUdToJ7qNlcsjlbR6U1eHEwgEAYq/b4NihsUDXEtC/j5VgqFMlbUKRVU8Mlw+PPghjc2NpCekk5ma2f/CAT8Zfx2P2xopuljC0aPHkSUZWZKwWW1U11RSUHQKh6IjdPL9QM+RSqqzeUDkFggEQwdhsAgEAcA1Kdew7cI2okxRnUanWJosbMrehOpUmTl8JulJ6Ww/tZ13976LikqoIZTlk5f3m3w6jRaTohBq0BMTEoyiqCioOJ0ONOePokEldfwid/ueIpUkUYdHIBB4iTBYPEAVXreCfiZEH8LCYQspbyzny/wvGWYexuiI0QC8s/cd6m313DT9JpwOJ1GhUQDMHzcfAEVReP/A+/0uY2S4mXqblfjhaYBrmaewqAjjhBSSksa3a9tTpJLso7wwAoHgykEYLB4i7BXBQBATFMOi1EXk1ebx0u6XMGAgLSKNuWPndtlHlmVOlZ/i2IVjTEyZ6HOZ0tLSWLt2LdPGjeT1119n5cqVbeoHaUDrfcVlp70ZFCeImRaBQOAhgevpF0AEgne04MoiLSyN+VHzuXPWnd0aKy08svwRTpacdPVNS+O5555rtz8zM5NHH33UKxlsdhsfH/oYS5MFgDU3LmXevHnt6geNHDmyXR+nvZnG4kJUqwXF1oCjqZHmRivWOiuN5RVYTuyjcvtHRFvtHN222St5BALBlY0wWDxARRQ/FAxOCqoKUBTF637v7n2XTw5/gs1pI8gQBEBImNkdIZSenk5mZibZ2dncnbWYsi8/YFh8LL/52Y+wXsyjdM8uKnbvIDNjIg//2900HvkcW/4xVFMUoTOXkxN9Leax83ytrkAgGMKIJSGBIECRJAlVVT0uC2HUGXln7ztYrK4ZEVuzjbf2vEVSRFKn7RVF4e29b6OVXZeBlkg4p+pkTNwYpqVN483db7r3X46jyYatug4pZhyxi65HNj5I6JgMIqdd7W6jDTYTlDqGyDntc+CGhxuw1IlIIYFgsBAICw3CYPEAVRVhzYKBJygoiIaGBkJCQjxqvzLTZRT8RP4Jh/IP8e6Bd4kLjWNK4hSqGqvIrcjls8OfYW22UtZQRrgpnKXpS4k2R3c6nqIoVDRWYHfa2Ze7j9mprTMi1to6ao+fp3T7AaLnTPFat3Pna1hyTarX/QQCgf/wd009YbB4gFgSEviDmJgYcnNzGTNmjFf9QowhZA7LZNmEZWhkDREhEQRpgogKiuLq0VdjNBgxaHp2lK1urCbSGElMTAzNRVZ0DXqqNm7G0tBIflEhQatuZtjqBV7rVVRWT0ykibBQ7511+xt/X5AFAkHXCB8WgSBA0el0GAwG6urqvOoXExNDcXEx0eZoIkIisFgsFOQXYA4yExYU5pGxAhAVEsWds+9k2dJlbPt6B/Wpo7g4MYV1n76BRqdDuuzyIctyBwf1zio5V1uaiYoweqWTQCAQCIPFA1RVFQtCAr+QmppKQUGBV30WLlzI66+/zjfffMOxY8dYs2ZNuyyzntA20mj9+vVMz5jCggULmDNnDqtXryYtJa3Db6LFUGrh8nT8LYQH6ai02LySRyAQCMSSkEAQ4CQnJ3PhwgVSUlI8at9TlllvCQkJ4b8feZLiB+9h9erVrFmzhuWZyzFcNkvSUzr+FhLjg9m192Kv5elPRAoDgSBwEQaLh4i1bYG/CAsLo7i4GLvdjk6n67F9T1lmveXc7hMMSx/ebpuqdvTr8tRQ2rGriKtmJPRaHoFAcGUiDBYPcEUJCQT+Y/To0Zw5c4bx48f33NjH2BtsFJ0qoNFST2H2KfI276W6qJzkxdMIJdTdzhNDqb6hmapqKwvmeDZbNNCIBxOBoHMCYe5R+LAIBIMAjUZDWFgYVVVVA3K8FgdaVVUJStRTVHOeZkczUaOSOXrmDLmVRWiNPc/2XM6WL3K5/trhPTcUCASCyxAGiweoiCkWgf9JTEykuLh4QPwsYmJiOHHkCNs++xinRsuMBYsoq6jAFBJCXFoyN/7H/UTER3k9rl6vQQ6ERzWBQDDo8MpgefHFF8nIyMBsNmM2m8nKymLz5tZ6IJIkdfr39NNPdzvu+++/T3p6OgaDgfT0dDZt2tQ7bfoJsSQkCBTS0tLIy8vr9+NMHDuGDz/5BG1YJFaHkx/+8IduB9q+2Bt2h4r3hQIEAoHAS4MlOTmZ3/72t+zfv5/9+/ezcOFCVq1axfHjxwEoLi5u9/fXv/4VSZK46aabuhxz165d3Hrrrdx5550cPnyYO++8k1tuuYU9e/b0TTOBYAgSHByMw+HoNL9JX3E6nVSVlvDlR5t44IF/Y+GiRaxYsYLly5ezevXq1kKHfZjhWTgvhQ1vHqfZ5vCR1AKB4EpBUvs4vxwZGcnTTz/NPffc02Hf6tWrqaur48svv+yy/6233orFYmk3U3PdddcRERHB22+/7bEcFouFsLAwamtrMZvN3inRA3/afp4Xt53n8K+u9em4AkFvcDqdnDt3jrFjx/pszLPHj1KYk0N4VDQZM69Co+3aH3/3h18xa/XCXh+rrKKBzzbnkJoaxsJ5w3o9Tn+w/Uw588fE+FsMgSDgePzTE2w/U84XD873+die3r97HSXkdDp57733aGhoICsrq8P+0tJSPvvsM1599dVux9m1axfr1q1rt23p0qXupFVdYbPZsNlak09ZLBbPhe8FdVY7q//wzw7bO7X2OrEBO2vXlamodtK6s7bdmZo9WaG9tVO7P2b3Y/ZW3u5k7VGLfjhmT30jgvT864KRGLSyq53a0kdFVV2fQ0t/VXV9amqbhi37Xf8v3+Z6X1rayJHaPLQ6bZdj0mn/VjmabVbOnTiO3mBEkiTSxk6mADi850Kbth0/j6IKOPj5KfRGfbefUbekBfPB0Yucdjaj0Ug91urq6bvlK86XN3C6xIIsSRi0MnqtjEGrwaCVMeo0GHRyi0AdPs+W89P2s297bhRVdZ/nzs5H2/Pb9uvXErgkSa2fkiS56pu5/re0kQAVRXUdy6m4xlXU1m3qpdeufa3bFZVL71WcSvu2bfc7lfZtW8fl0r7W/Zfrplx60fZzcrdt85kpyuWfCW692v5e3ONc9lkrnZ2DNp+/eukDbretq/HabWs9vl4jEx3iyhjtvPS5tOjf8rrtOZMk159RqyHUqCXEqCPUqCXUoCXYoEUjS+3Oqyy1P8ctY7Wc5Zbz7j6G+3vgei1Ll8Zo+Y5IrWPKLe4atLwG+dL3x70fkOVLNfQubSuqbvLqt9QfeG2wHD16lKysLKxWKyEhIWzatIn09PQO7V599VVCQ0O58cYbux2vpKSEuLi4dtvi4uIoKSnptt+TTz7JY4895q34vWLx+DjyKxu7vIl1HQnZ+Y7uIie72tVVn+4u9L05Tmvf3nnt9NStP+Tt8ZjdNOi2a7fydL1z64kS/uX1A90L5RO8T77WenMDVJAkA5KkIqHCWdfSrvvid+liJbXp6yYvt8sP3tNvjqqqfFlcE1B1ulou9IoKzQ6FZufQ87hpd0O79F+WJDQtNy9Zardf07at3NK3tV/rTa91f7sbNa03xrbfKfe2y26sbfu1vpfQyG2NNKndDbWljXxZv5abbeuYbY7ZyXa5xShot639eBISVruTyoZmZAnX5yNL7v9aWbpkALQ3ShUVrHYndVYHFXU28ioaqLPaqbc52xhwLQZUq9GltBixtBqyLQZVy/a2xlmL0dgfzEiL6J+BPcRrg2Xs2LFkZ2dTU1PD+++/z5o1a9i+fXsHo+Wvf/0rd9xxB0ZjzzVDLr+hqKra4w1z/fr1PPjgg+73FovF40yg3jIqNoQnb5zUL2MLhh4PLhlDRb1r9u/yJ2HXxsufji9/crp0EZZos739xbVlbDrZdnl76PgbE3iGoqg0OxWsdic2h+s/XP7k2/nNr+0NTu6kTcs57uz8tj1dXc3iqCodZhE6GCFy2yfuVjkEQ5+WmSGlk9mkdtuUVoOqreHkMpba74sK9m/BUq8NFr1ez6hRowCYPn06+/bt4/nnn+fPf/6zu80333zD6dOnOySR6oz4+PgOsyllZWUdZl0ux2AwYDAEXrVXgUCvlUkMN/lbDIEPkGUJo6zBqPOuFpNA4G/cy0NDKMa1z3lYVFVt50sC8PLLLzNt2jQmT57cY/+srCw+//zzdtu2bt3K7Nmz+yqaQCAQCASCIYJXMywPPfQQy5YtIyUlhbq6OjZu3Mi2bdvYsmWLu43FYuG9997jf/7nfzod46677iIpKYknn3wSgJ/97GfMmzePp556ilWrVvHRRx/xxRdf8O233/ZBLYFAIBAIBEMJrwyW0tJS7rzzToqLiwkLCyMjI4MtW7awZMkSd5uNGzeiqiq33XZbp2MUFBQgy60TO7Nnz2bjxo08/PDDPPLII4wcOZJ33nmHq666qpcqCQQCgUAgGGr0OQ9LoNCfeVgEAoFAIBD0D57ev0UtIYFAIBAIBAGPMFgEAoFAIBAEPMJgEQgEAoFAEPAIg0UgEAgEAkHAIwwWgUAgEAgEAY8wWAQCgUAgEAQ8wmARCAQCgUAQ8AiDRSAQCAQCQcAjDBaBQCAQCAQBj9fVmgOVloS9FovFz5IIBAKBQCDwlJb7dk+J94eMwVJXVwdASkqKnyURCAQCgUDgLXV1dYSFhXW5f8jUElIUhYsXLxIaGookSf12HIvFQkpKChcuXLgiaxZd6fqD+AyE/kL/K1l/EJ+Br/VXVZW6ujoSExPbFUe+nCEzwyLLMsnJyQN2PLPZfEV+UVu40vUH8RkI/YX+V7L+ID4DX+rf3cxKC8LpViAQCAQCQcAjDBaBQCAQCAQBjzBYvMRgMPCrX/0Kg8Hgb1H8wpWuP4jPQOgv9L+S9QfxGfhL/yHjdCsQCAQCgWDoImZYBAKBQCAQBDzCYBEIBAKBQBDwCINFIBAIBAJBwCMMFoFAIBAIBAGPMFi64YknnmD27NkEBQURHh7eaZuCggJWrlxJcHAw0dHR/PSnP6W5ubldm3fffZfMzEyCgoJITU3l6aefHgDp+46v9P/HP/7BrFmzCA0NJSYmhptuuonc3NwB0KBv+EL/Rx99FEmSOvwFBwcPkBa9x1fnX1VVfve73zFmzBgMBgMpKSn85je/GQAN+oYv9M/Ly+v0/G/ZsmWAtOgbvvoOtHDu3DlCQ0O7HCvQ8IX+p0+f5pprriEuLg6j0ciIESN4+OGHsdvtA6RF7/GF/tu2bWPVqlUkJCQQHBxMZmYmb775Zq/kGTKZbvuD5uZmvvvd75KVlcXLL7/cYb/T6eT6668nJiaGb7/9lsrKStasWYOqqvz+978HYPPmzdxxxx38/ve/59prr+XkyZPce++9mEwmHnjggYFWySt8oX9OTg6rVq3iwQcf5M0336S2tpZ169Zx4403cujQoYFWySt8of8vfvELfvSjH7Xrt2jRImbMmDEgOvQFX+gP8LOf/YytW7fyu9/9jkmTJlFbW0tFRcVAqtIrfKU/wBdffMGECRPc7yMjI/tdfl/gy8/Abrdz2223MXfuXHbu3DlQKvQJX+iv0+m46667mDp1KuHh4Rw+fJj77rsPRVEC3nD3hf47d+4kIyOD//iP/yAuLo7PPvuMu+66C7PZzMqVK70TSBX0yCuvvKKGhYV12P73v/9dlWVZLSoqcm97++23VYPBoNbW1qqqqqq33XabevPNN7fr9+yzz6rJycmqoij9Krev6Iv+7733nqrValWn0+lu8/HHH6uSJKnNzc39Lrsv6Iv+l5Odna0C6o4dO/pLXJ/TF/1PnDiharVa9dSpUwMlrs/pi/65ubkqoB46dGiApO0ffPEb+Pd//3f1+9//fpdjBTK+vAaoqqquW7dOvfrqq/tD1H7B1/ovX75c/eEPf+i1HGJJqA/s2rWLiRMnkpiY6N62dOlSbDYbBw4cAMBms2E0Gtv1M5lMFBYWkp+fP6Dy+hpP9J8+fToajYZXXnkFp9NJbW0tr7/+Otdeey06nc5fovsET/S/nJdeeokxY8Ywd+7cgRKz3/BE/08++YQRI0bw6aefMnz4cNLS0rj33nupqqryl9g+w5vzf8MNNxAbG8ucOXP429/+NtCi9huefgZfffUV7733Hn/4wx/8IWa/0ZtrwLlz59iyZQvz588fKDH7jd7oD1BbW9urWUZhsPSBkpIS4uLi2m2LiIhAr9dTUlICuE7eBx98wJdffomiKJw5c4bnnnsOgOLi4oEW2ad4on9aWhpbt27loYcewmAwEB4eTmFhIRs3bvSHyD7FE/3bYrPZePPNN7nnnnsGSsR+xRP9c3JyyM/P57333uO1115jw4YNHDhwgJtvvtkfIvsUT/QPCQnhmWee4W9/+xt///vfWbRoEbfeeitvvPGGP0T2OZ58BpWVlfzgBz9gw4YNQ65QoDfXgNmzZ2M0Ghk9ejRz587l17/+9UCK2i94ew0E+Nvf/sa+ffv44Q9/6PXxrjiDpSsnyLZ/+/fv93g8SZI6bFNV1b39vvvu44EHHmDFihXo9XpmzZrF9773PQA0Go1vlPKCgda/pKSEe++9lzVr1rBv3z62b9+OXq/n5ptvRvVDkuWB1r8tH3zwAXV1ddx111190qEvDLT+iqJgs9l47bXXmDt3LgsWLODll1/m66+/5vTp0z7Ty1MGWv/o6GjWrVvHzJkzmT59Or/+9a/58Y9/zH//93/7TCdv8cc18Pbbb2fevHk+06Ev+Osa8M4773Dw4EHeeustPvvsM373u9/1WZfe4M9r4LZt2/jBD37AX/7yl3Y+XZ5yxTndPvDAA26DoSvS0tI8Gis+Pp49e/a021ZdXY3dbndbnZIk8dRTT/Gb3/yGkpISYmJi+PLLL706ji8ZaP3/8Ic/YDab212g33jjDVJSUtizZw+zZs3yToE+MtD6t+Wll15ixYoVxMfHeyyvrxlo/RMSEtBqtYwZM8bdZvz48YArumDs2LFeSN93/Hn+W5g1axYvvfSSR8foDwb6M/jqq6/4+OOP3TdoVVVRFAWtVsv//d//cffdd3uvRB/w13cgJSUFgPT0dJxOJ/fffz8///nPB/zB1V/6b9++nZUrV/LMM8/0+qHtijNYoqOjiY6O9slYWVlZPPHEExQXF5OQkADA1q1bMRgMTJs2rV1bjUZDUlISAG+//TZZWVnExsb6RA5vGGj9GxsbO/wgW94riuITObzBX+c/NzeXr7/+mo8//tgnx+4tA63/nDlzcDgcnD9/npEjRwJw5swZAFJTU30ihzf46/y35dChQ+72/mCgP4Ndu3bhdDrdfT766COeeuopdu7c6b4mDiSB8B1QVRW73e6XWWZ/6L9t2zZWrFjBU089xf3339/7A3rtpnsFkZ+frx46dEh97LHH1JCQEPXQoUPqoUOH1Lq6OlVVVdXhcKgTJ05UFy1apB48eFD94osv1OTkZPWBBx5wj1FeXq6++OKL6smTJ9VDhw6pP/3pT1Wj0aju2bPHX2p5jC/0//LLL1VJktTHHntMPXPmjHrgwAF16dKlampqqtrY2Ogv1TzCF/q38PDDD6uJiYmqw+EYaDV6jS/0dzqd6tSpU9V58+apBw8eVPfv369eddVV6pIlS/yllsf4Qv8NGzaob775pnrixAn11KlT6tNPP63qdDr1mWee8ZdaXuHL30ALgylKyBf6v/HGG+o777yjnjhxQj1//rz67rvvqklJSeodd9zhL7U8xhf6f/3112pQUJC6fv16tbi42P1XWVnptTzCYOmGNWvWqECHv6+//trdJj8/X73++utVk8mkRkZGqg888IBqtVrd+8vLy9VZs2apwcHBalBQkLpo0SJ19+7dftDGe3yhv6q6wtymTJmiBgcHqzExMeoNN9ygnjx5coC18R5f6e90OtXk5GT1oYceGmAN+oav9C8qKlJvvPFGNSQkRI2Li1N/8IMf9OpiNdD4Qv8NGzao48ePV4OCgtTQ0FB12rRp6uuvv+4HbXqHr74DbRlMBosv9N+4caM6depUNSQkRA0ODlbT09PV3/zmN2pTU5MfNPIOX+jf1Rjz58/3Wh5JVf0wJyUQCAQCgUDgBVdclJBAIBAIBILBhzBYBAKBQCAQBDzCYBEIBAKBQBDwCINFIBAIBAJBwCMMFoFAIBAIBAGPMFgEAoFAIBAEPMJgEQgEAoFAEPAIg0UgEAgEAkHAIwwWgUAgEAgEAY8wWAQCgUAgEAQ8wmARCAQCgUAQ8AiDRSAQCAQCQcDz/wPf4518fqopTgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on HD 0\n",
      "working on HD 400\n",
      "working on HD 800\n",
      "working on HD 1200\n",
      "working on HD 1600\n",
      "working on HD 2000\n",
      "working on HD 2400\n",
      "working on HD 2800\n",
      "out of  3097 drawn districts, number of discontig, has-Enclave, or both is 0 0 0\n"
     ]
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.show()\n",
    "nEnclavy, nDiscontig, nBoth = 0,0,0\n",
    "hasEnclave, hasDiscontig, hasBoth = list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%400 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken and noEnclave:\n",
    "        nDiscontig +=1\n",
    "        hasDiscontig.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        nBoth +=1\n",
    "        hasBoth.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        nEnclavy += 1\n",
    "        hasEnclave.append(t)\n",
    "print(\"out of \",len(popHDlist),\"drawn districts, number of discontig, has-Enclave, or both is\",nDiscontig,nEnclavy,nBoth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "114705bb-9640-45f1-9f25-030030efaa63",
   "metadata": {},
   "outputs": [],
   "source": [
    "#below here -- working on tightening use distro while squaring up pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "5d7d8519-eb3d-4345-9ac6-ab888e61c348",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 0.61986 0.17504\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6599c5fb-050d-4db7-b99d-3ba91219c889",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking on our corner clusters and unit county usage\n",
      "usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\n",
      "0.68864     0     3499 0.5\n",
      "0.85722     1     1379 0.5\n",
      "1.15232     2     5922 0.5\n",
      "0.89953     3     4704 0.5\n",
      "0.98291     4     5808 0.5\n",
      "0.72171     5     788 0.5\n",
      "0.68639     6     6820 0.5\n",
      "1.72622     7     5675 0.5\n",
      "0.65762     8     865 0.5\n",
      "0.74705     9     4874 0.5\n",
      "0.71686     10     6368 0.5\n",
      "1.03504     2820     44650 0.25\n",
      "1.01799     2821     65547 0.25\n",
      "0.89303     2822     105949 0.25\n",
      "0.98067     2823     42401 0.25\n"
     ]
    }
   ],
   "source": [
    "print(\"checking on our corner clusters and unit county usage\")\n",
    "print(\"usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\")\n",
    "for u in range(nUnits):\n",
    "    if int(allUnits[u]) != allUnits[u] :\n",
    "        print(r5(unitUse[u]),\"   \",u,\"   \",int(unitPop[u]), allUnits[u]%1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "b1971853-bda7-49a4-9f25-1bdfd5e75aa2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1600\n",
      "working on avg unit-to-HDcp dist for HD 2400\n"
     ]
    }
   ],
   "source": [
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "f179943a-ef19-4036-a8c6-5ab7b1f97bf8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NjY1yOp1KTU3ViRMnrExBQYEqKytVUVGhuro6nTx5UpmZmRoYGLAy2dnZamlpUVVVlaqqqtTS0iK3221tHxgYUEZGhk6dOqW6ujpVVFRo69atWrFihZXp6elRamqqXC6XGhsbtXHjRpWWlqqsrOx85goAAIwxQWYAyyOrV6/Wn//8Z7322mtn3W6aplwulwoKCvTwww9L+nj1JyYmRo8//riWLl0qr9erG264Qc8//7zuvfdeSdKRI0cUGxur7du3Kz09XQcOHFB8fLwaGhqUlJQkSWpoaFBycrLeeOMNxcXFaceOHcrMzFR7e7tcLpckqaKiQjk5Oeru7lZERIQ2bdqkoqIiHT16VA6HQ5K0bt06bdy4UR0dHQoKCjrnMff09MgwDHm9XkVERIx0qoALNmX1tsu2r0PrMi7bvgDgchjp93dIIB/6u9/9Tunp6frGN76h2tpaTZo0SXl5ecrNzZUkHTx4UF1dXUpLS7Pe43A4lJKSot27d2vp0qVqampSf3+/X8blcikhIUG7d+9Wenq66uvrZRiGVYIkaebMmTIMQ7t371ZcXJzq6+uVkJBglSBJSk9Pl8/nU1NTk+6++27V19crJSXFKkGDmaKiIh06dEhTp04dcow+n08+n89vIoGxbiSli7IEYCwK6NTYO++8o02bNumWW27RH/7wBz344IPKz8/Xr371K0lSV1eXJCkmJsbvfTExMda2rq4uhYaGKjIycthMdHT0kP1HR0f7Zc7cT2RkpEJDQ4fNDD4fzJyppKTEui7JMAzFxsaeY1YAAMBoFVAROn36tO644w4VFxfr85//vJYuXarc3Fxt2rTJL3fmKSfTNM95GurMzNnyFyMzeCbwk8ZTVFQkr9drPdrb24cdNwAAGL0CKkITJ05UfHy832vTpk3T4cOHJUlOp1PS0NWW7u5uayXG6XSqr69PHo9n2MzRo0eH7P/YsWN+mTP34/F41N/fP2ymu7tb0tBVq0EOh0MRERF+DwAAMDYFVIRmz56tN9980++1t956SzfddJMkaerUqXI6naqpqbG29/X1qba2VrNmzZIkJSYmaty4cX6Zzs5OtbW1WZnk5GR5vV7t3bvXyuzZs0der9cv09bWps7OTitTXV0th8OhxMREK7Nr1y6/W+qrq6vlcrk0ZcqUQA4dAACMQQEVoe9+97tqaGhQcXGx/ud//kcvvviifv7zn2vZsmWSPj7dVFBQoOLiYlVWVqqtrU05OTkaP368srOzJUmGYWjJkiVasWKFdu7cqebmZi1atEjTp0/XvHnzJH28yjR//nzl5uaqoaFBDQ0Nys3NVWZmpuLi4iRJaWlpio+Pl9vtVnNzs3bu3KmVK1cqNzfXWsXJzs6Ww+FQTk6O2traVFlZqeLiYhUWFo7ojjEAADC2BXTX2Be+8AVVVlaqqKhIa9eu1dSpU/XUU0/p/vvvtzKrVq1Sb2+v8vLy5PF4lJSUpOrqak2YMMHKbNiwQSEhIVq4cKF6e3s1d+5cbd68WcHBwVZmy5Ytys/Pt+4uy8rKUnl5ubU9ODhY27ZtU15enmbPnq2wsDBlZ2ertLTUyhiGoZqaGi1btkwzZsxQZGSkCgsLVVhYGPhMAQCAMSeg3xGyI35HCFfK5fwdoZHg9nkAo8lIv7/5W2MAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2KEIAAMC2AipCa9asUVBQkN/D6XRa203T1Jo1a+RyuRQWFqY5c+Zo3759fp/h8/m0fPlyRUVFKTw8XFlZWero6PDLeDweud1uGYYhwzDkdrt1/Phxv8zhw4e1YMEChYeHKyoqSvn5+err6/PLtLa2KiUlRWFhYZo0aZLWrl0r0zQDOWQAADCGBbwi9NnPfladnZ3Wo7W11dq2fv16lZWVqby8XI2NjXI6nUpNTdWJEyesTEFBgSorK1VRUaG6ujqdPHlSmZmZGhgYsDLZ2dlqaWlRVVWVqqqq1NLSIrfbbW0fGBhQRkaGTp06pbq6OlVUVGjr1q1asWKFlenp6VFqaqpcLpcaGxu1ceNGlZaWqqysLOBJAgAAY1NIwG8ICfFbBRpkmqaeeuopPfLII/ra174mSfrlL3+pmJgYvfjii1q6dKm8Xq+effZZPf/885o3b54k6YUXXlBsbKxeffVVpaen68CBA6qqqlJDQ4OSkpIkSb/4xS+UnJysN998U3Fxcaqurtb+/fvV3t4ul8slSXryySeVk5OjH//4x4qIiNCWLVv04YcfavPmzXI4HEpISNBbb72lsrIyFRYWKigo6KzH5/P55PP5rOc9PT2BThEAABglAl4Revvtt+VyuTR16lR985vf1DvvvCNJOnjwoLq6upSWlmZlHQ6HUlJStHv3bklSU1OT+vv7/TIul0sJCQlWpr6+XoZhWCVIkmbOnCnDMPwyCQkJVgmSpPT0dPl8PjU1NVmZlJQUORwOv8yRI0d06NChTzy+kpIS65ScYRiKjY0NdIoAAMAoEVARSkpK0q9+9Sv94Q9/0C9+8Qt1dXVp1qxZev/999XV1SVJiomJ8XtPTEyMta2rq0uhoaGKjIwcNhMdHT1k39HR0X6ZM/cTGRmp0NDQYTODzwczZ1NUVCSv12s92tvbh58UAAAwagV0auyee+6x/vP06dOVnJysT3/60/rlL3+pmTNnStKQU06maX7iaahPypwtfzEygxdKDzceh8Pht4oEAADGrgu6fT48PFzTp0/X22+/bV03dOZqS3d3t7US43Q61dfXJ4/HM2zm6NGjQ/Z17Ngxv8yZ+/F4POrv7x82093dLWnoqhUAALCnCypCPp9PBw4c0MSJEzV16lQ5nU7V1NRY2/v6+lRbW6tZs2ZJkhITEzVu3Di/TGdnp9ra2qxMcnKyvF6v9u7da2X27Nkjr9frl2lra1NnZ6eVqa6ulsPhUGJiopXZtWuX3y311dXVcrlcmjJlyoUcNgAAGCMCKkIrV65UbW2tDh48qD179ujrX/+6enp6tHjxYgUFBamgoEDFxcWqrKxUW1ubcnJyNH78eGVnZ0uSDMPQkiVLtGLFCu3cuVPNzc1atGiRpk+fbt1FNm3aNM2fP1+5ublqaGhQQ0ODcnNzlZmZqbi4OElSWlqa4uPj5Xa71dzcrJ07d2rlypXKzc1VRESEpI9vwXc4HMrJyVFbW5sqKytVXFw87B1jAADAXgK6Rqijo0P33Xef3nvvPd1www2aOXOmGhoadNNNN0mSVq1apd7eXuXl5cnj8SgpKUnV1dWaMGGC9RkbNmxQSEiIFi5cqN7eXs2dO1ebN29WcHCwldmyZYvy8/Otu8uysrJUXl5ubQ8ODta2bduUl5en2bNnKywsTNnZ2SotLbUyhmGopqZGy5Yt04wZMxQZGanCwkIVFhae30wBAIAxJ8jkp5aH1dPTI8Mw5PV6rdUm4HKYsnrblR6Cn0PrMq70EABgxEb6/c3fGgMAALZFEQIAALZFEQIAALZFEQIAALYV8B9dBexsJBcwc1ExAIwerAgBAADboggBAADboggBAADboggBAADboggBAADboggBAADboggBAADboggBAADboggBAADboggBAADboggBAADboggBAADb4o+uAlfASP54KwDg0mNFCAAA2BYrQsBFNlZXe0ZyXIfWZVyGkQDAxcOKEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsC2KEAAAsK2QKz0AAGPHlNXbzpk5tC7jMowEAEbmglaESkpKFBQUpIKCAus10zS1Zs0auVwuhYWFac6cOdq3b5/f+3w+n5YvX66oqCiFh4crKytLHR0dfhmPxyO32y3DMGQYhtxut44fP+6XOXz4sBYsWKDw8HBFRUUpPz9ffX19fpnW1lalpKQoLCxMkyZN0tq1a2Wa5oUcNgAAGCPOuwg1Njbq5z//uW677Ta/19evX6+ysjKVl5ersbFRTqdTqampOnHihJUpKChQZWWlKioqVFdXp5MnTyozM1MDAwNWJjs7Wy0tLaqqqlJVVZVaWlrkdrut7QMDA8rIyNCpU6dUV1eniooKbd26VStWrLAyPT09Sk1NlcvlUmNjozZu3KjS0lKVlZWd72EDAIAxJMg8j+WRkydP6o477tDTTz+tH/3oR/rc5z6np556SqZpyuVyqaCgQA8//LCkj1d/YmJi9Pjjj2vp0qXyer264YYb9Pzzz+vee++VJB05ckSxsbHavn270tPTdeDAAcXHx6uhoUFJSUmSpIaGBiUnJ+uNN95QXFycduzYoczMTLW3t8vlckmSKioqlJOTo+7ubkVERGjTpk0qKirS0aNH5XA4JEnr1q3Txo0b1dHRoaCgoHMea09PjwzDkNfrVURERKBThTFmJKd+MDxOjQG4HEb6/X1eK0LLli1TRkaG5s2b5/f6wYMH1dXVpbS0NOs1h8OhlJQU7d69W5LU1NSk/v5+v4zL5VJCQoKVqa+vl2EYVgmSpJkzZ8owDL9MQkKCVYIkKT09XT6fT01NTVYmJSXFKkGDmSNHjujQoUNnPTafz6eenh6/BwAAGJsCLkIVFRX6y1/+opKSkiHburq6JEkxMTF+r8fExFjburq6FBoaqsjIyGEz0dHRQz4/OjraL3PmfiIjIxUaGjpsZvD5YOZMJSUl1nVJhmEoNjb2rDkAADD6BVSE2tvb9Z3vfEcvvPCCrr322k/MnXnKyTTNc56GOjNztvzFyAyeCfyk8RQVFcnr9VqP9vb2YccNAABGr4CKUFNTk7q7u5WYmKiQkBCFhISotrZWP/nJTxQSEvKJqy3d3d3WNqfTqb6+Pnk8nmEzR48eHbL/Y8eO+WXO3I/H41F/f/+wme7ubklDV60GORwORURE+D0AAMDYFFARmjt3rlpbW9XS0mI9ZsyYofvvv18tLS26+eab5XQ6VVNTY72nr69PtbW1mjVrliQpMTFR48aN88t0dnaqra3NyiQnJ8vr9Wrv3r1WZs+ePfJ6vX6ZtrY2dXZ2Wpnq6mo5HA4lJiZamV27dvndUl9dXS2Xy6UpU6YEcugAAGAMCugHFSdMmKCEhAS/18LDw3X99ddbrxcUFKi4uFi33HKLbrnlFhUXF2v8+PHKzs6WJBmGoSVLlmjFihW6/vrrdd1112nlypWaPn26dfH1tGnTNH/+fOXm5upnP/uZJOnf/u3flJmZqbi4OElSWlqa4uPj5Xa79cQTT+iDDz7QypUrlZuba63iZGdn67HHHlNOTo6+//3v6+2331ZxcbF++MMfjuiOMQAAMLZd9F+WXrVqlXp7e5WXlyePx6OkpCRVV1drwoQJVmbDhg0KCQnRwoUL1dvbq7lz52rz5s0KDg62Mlu2bFF+fr51d1lWVpbKy8ut7cHBwdq2bZvy8vI0e/ZshYWFKTs7W6WlpVbGMAzV1NRo2bJlmjFjhiIjI1VYWKjCwsKLfdgAAGAUOq/fEbITfkcI/xe/I3Th+B0hAJfDJf0dIQAAgLGAIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGyLIgQAAGwroCK0adMm3XbbbYqIiFBERISSk5O1Y8cOa7tpmlqzZo1cLpfCwsI0Z84c7du3z+8zfD6fli9frqioKIWHhysrK0sdHR1+GY/HI7fbLcMwZBiG3G63jh8/7pc5fPiwFixYoPDwcEVFRSk/P199fX1+mdbWVqWkpCgsLEyTJk3S2rVrZZpmIIcMAADGsICK0OTJk7Vu3Tq9/vrrev311/XlL39Z//Iv/2KVnfXr16usrEzl5eVqbGyU0+lUamqqTpw4YX1GQUGBKisrVVFRobq6Op08eVKZmZkaGBiwMtnZ2WppaVFVVZWqqqrU0tIit9ttbR8YGFBGRoZOnTqluro6VVRUaOvWrVqxYoWV6enpUWpqqlwulxobG7Vx40aVlpaqrKzsvCcLAACMLUHmBS6RXHfddXriiSf0wAMPyOVyqaCgQA8//LCkj1d/YmJi9Pjjj2vp0qXyer264YYb9Pzzz+vee++VJB05ckSxsbHavn270tPTdeDAAcXHx6uhoUFJSUmSpIaGBiUnJ+uNN95QXFycduzYoczMTLW3t8vlckmSKioqlJOTo+7ubkVERGjTpk0qKirS0aNH5XA4JEnr1q3Txo0b1dHRoaCgoBEdX09PjwzDkNfrVURExIVMFcaAKau3XekhjHqH1mVc6SEAsIGRfn+f9zVCAwMDqqio0KlTp5ScnKyDBw+qq6tLaWlpVsbhcCglJUW7d++WJDU1Nam/v98v43K5lJCQYGXq6+tlGIZVgiRp5syZMgzDL5OQkGCVIElKT0+Xz+dTU1OTlUlJSbFK0GDmyJEjOnTo0Ccel8/nU09Pj98DAACMTQEXodbWVv3TP/2THA6HHnzwQVVWVio+Pl5dXV2SpJiYGL98TEyMta2rq0uhoaGKjIwcNhMdHT1kv9HR0X6ZM/cTGRmp0NDQYTODzwczZ1NSUmJdm2QYhmJjY4efEAAAMGoFXITi4uLU0tKihoYG/fu//7sWL16s/fv3W9vPPOVkmuY5T0OdmTlb/mJkBs8CDjeeoqIieb1e69He3j7s2AEAwOgVcBEKDQ3VP//zP2vGjBkqKSnR7bffrv/4j/+Q0+mUNHS1pbu721qJcTqd6uvrk8fjGTZz9OjRIfs9duyYX+bM/Xg8HvX39w+b6e7uljR01er/cjgc1l1xgw8AADA2XfDvCJmmKZ/Pp6lTp8rpdKqmpsba1tfXp9raWs2aNUuSlJiYqHHjxvllOjs71dbWZmWSk5Pl9Xq1d+9eK7Nnzx55vV6/TFtbmzo7O61MdXW1HA6HEhMTrcyuXbv8bqmvrq6Wy+XSlClTLvSwAQDAGBBQEfr+97+v1157TYcOHVJra6seeeQR/elPf9L999+voKAgFRQUqLi4WJWVlWpra1NOTo7Gjx+v7OxsSZJhGFqyZIlWrFihnTt3qrm5WYsWLdL06dM1b948SdK0adM0f/585ebmqqGhQQ0NDcrNzVVmZqbi4uIkSWlpaYqPj5fb7VZzc7N27typlStXKjc311rByc7OlsPhUE5Ojtra2lRZWani4mIVFhaO+I4xAAAwtoUEEj569Kjcbrc6OztlGIZuu+02VVVVKTU1VZK0atUq9fb2Ki8vTx6PR0lJSaqurtaECROsz9iwYYNCQkK0cOFC9fb2au7cudq8ebOCg4OtzJYtW5Sfn2/dXZaVlaXy8nJre3BwsLZt26a8vDzNnj1bYWFhys7OVmlpqZUxDEM1NTVatmyZZsyYocjISBUWFqqwsPD8ZgoAAIw5F/w7QmMdvyOE/4vfEbpw/I4QgMvhkv+OEAAAwGhHEQIAALZFEQIAALZFEQIAALZFEQIAALZFEQIAALYV0O8IAaPVSG5757ZuALAfVoQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtUYQAAIBtBVSESkpK9IUvfEETJkxQdHS0vvrVr+rNN9/0y5imqTVr1sjlciksLExz5szRvn37/DI+n0/Lly9XVFSUwsPDlZWVpY6ODr+Mx+OR2+2WYRgyDENut1vHjx/3yxw+fFgLFixQeHi4oqKilJ+fr76+Pr9Ma2urUlJSFBYWpkmTJmnt2rUyTTOQwwYAAGNUQEWotrZWy5YtU0NDg2pqavTRRx8pLS1Np06dsjLr169XWVmZysvL1djYKKfTqdTUVJ04ccLKFBQUqLKyUhUVFaqrq9PJkyeVmZmpgYEBK5Odna2WlhZVVVWpqqpKLS0tcrvd1vaBgQFlZGTo1KlTqqurU0VFhbZu3aoVK1ZYmZ6eHqWmpsrlcqmxsVEbN25UaWmpysrKzmuyAADA2BJkXsDyyLFjxxQdHa3a2lrdddddMk1TLpdLBQUFevjhhyV9vPoTExOjxx9/XEuXLpXX69UNN9yg559/Xvfee68k6ciRI4qNjdX27duVnp6uAwcOKD4+Xg0NDUpKSpIkNTQ0KDk5WW+88Ybi4uK0Y8cOZWZmqr29XS6XS5JUUVGhnJwcdXd3KyIiQps2bVJRUZGOHj0qh8MhSVq3bp02btyojo4OBQUFnfMYe3p6ZBiGvF6vIiIizneqcIVNWb3tnJlD6zIuyudgeCOZZwC4UCP9/g65kJ14vV5J0nXXXSdJOnjwoLq6upSWlmZlHA6HUlJStHv3bi1dulRNTU3q7+/3y7hcLiUkJGj37t1KT09XfX29DMOwSpAkzZw5U4ZhaPfu3YqLi1N9fb0SEhKsEiRJ6enp8vl8ampq0t133636+nqlpKRYJWgwU1RUpEOHDmnq1KlDjsnn88nn81nPe3p6LmSKMIpQcgDAfs77YmnTNFVYWKgvfelLSkhIkCR1dXVJkmJiYvyyMTEx1rauri6FhoYqMjJy2Ex0dPSQfUZHR/tlztxPZGSkQkNDh80MPh/MnKmkpMS6LskwDMXGxp5jJgAAwGh13kXooYce0l//+le99NJLQ7adecrJNM1znoY6M3O2/MXIDJ4J/KTxFBUVyev1Wo/29vZhxw0AAEav8ypCy5cv1+9+9zv98Y9/1OTJk63XnU6npKGrLd3d3dZKjNPpVF9fnzwez7CZo0ePDtnvsWPH/DJn7sfj8ai/v3/YTHd3t6Shq1aDHA6HIiIi/B4AAGBsCqgImaaphx56SK+88or+67/+a8g1NlOnTpXT6VRNTY31Wl9fn2prazVr1ixJUmJiosaNG+eX6ezsVFtbm5VJTk6W1+vV3r17rcyePXvk9Xr9Mm1tbers7LQy1dXVcjgcSkxMtDK7du3yu6W+urpaLpdLU6ZMCeTQAQDAGBRQEVq2bJleeOEFvfjii5owYYK6urrU1dWl3t5eSR+fbiooKFBxcbEqKyvV1tamnJwcjR8/XtnZ2ZIkwzC0ZMkSrVixQjt37lRzc7MWLVqk6dOna968eZKkadOmaf78+crNzVVDQ4MaGhqUm5urzMxMxcXFSZLS0tIUHx8vt9ut5uZm7dy5UytXrlRubq61ipOdnS2Hw6GcnBy1tbWpsrJSxcXFKiwsHNEdYwAAYGwL6K6xTZs2SZLmzJnj9/pzzz2nnJwcSdKqVavU29urvLw8eTweJSUlqbq6WhMmTLDyGzZsUEhIiBYuXKje3l7NnTtXmzdvVnBwsJXZsmWL8vPzrbvLsrKyVF5ebm0PDg7Wtm3blJeXp9mzZyssLEzZ2dkqLS21MoZhqKamRsuWLdOMGTMUGRmpwsJCFRYWBnLYAABgjLqg3xGyA35HaGzg1vjRhd8aAnChRvr9zd8aAwAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAtkURAgAAthVypQcADGfK6m3nzBxal3EZRgIAGItYEQIAALZFEQIAALZFEQIAALZFEQIAALZFEQIAALbFXWMY9UZyZxkAAGfDihAAALAtVoTGCH5vBwCAwLEiBAAAbIsiBAAAbIsiBAAAbIsiBAAAbIsiBAAAbIsiBAAAbCvgIrRr1y4tWLBALpdLQUFB+u1vf+u33TRNrVmzRi6XS2FhYZozZ4727dvnl/H5fFq+fLmioqIUHh6urKwsdXR0+GU8Ho/cbrcMw5BhGHK73Tp+/Lhf5vDhw1qwYIHCw8MVFRWl/Px89fX1+WVaW1uVkpKisLAwTZo0SWvXrpVpmoEeNgAAGIMCLkKnTp3S7bffrvLy8rNuX79+vcrKylReXq7GxkY5nU6lpqbqxIkTVqagoECVlZWqqKhQXV2dTp48qczMTA0MDFiZ7OxstbS0qKqqSlVVVWppaZHb7ba2DwwMKCMjQ6dOnVJdXZ0qKiq0detWrVixwsr09PQoNTVVLpdLjY2N2rhxo0pLS1VWVhboYQMAgDEo4B9UvOeee3TPPfecdZtpmnrqqaf0yCOP6Gtf+5ok6Ze//KViYmL04osvaunSpfJ6vXr22Wf1/PPPa968eZKkF154QbGxsXr11VeVnp6uAwcOqKqqSg0NDUpKSpIk/eIXv1BycrLefPNNxcXFqbq6Wvv371d7e7tcLpck6cknn1ROTo5+/OMfKyIiQlu2bNGHH36ozZs3y+FwKCEhQW+99ZbKyspUWFiooKCg85o0AAAwNlzUa4QOHjyorq4upaWlWa85HA6lpKRo9+7dkqSmpib19/f7ZVwulxISEqxMfX29DMOwSpAkzZw5U4Zh+GUSEhKsEiRJ6enp8vl8ampqsjIpKSlyOBx+mSNHjujQoUNnPQafz6eenh6/BwAAGJsuahHq6uqSJMXExPi9HhMTY23r6upSaGioIiMjh81ER0cP+fzo6Gi/zJn7iYyMVGho6LCZweeDmTOVlJRY1yUZhqHY2NhzHzgAABiVLsldY2eecjJN85ynoc7MnC1/MTKDF0p/0niKiork9XqtR3t7+7DjBgAAo9dFLUJOp1PS0NWW7u5uayXG6XSqr69PHo9n2MzRo0eHfP6xY8f8Mmfux+PxqL+/f9hMd3e3pKGrVoMcDociIiL8HgAAYGy6qEVo6tSpcjqdqqmpsV7r6+tTbW2tZs2aJUlKTEzUuHHj/DKdnZ1qa2uzMsnJyfJ6vdq7d6+V2bNnj7xer1+mra1NnZ2dVqa6uloOh0OJiYlWZteuXX631FdXV8vlcmnKlCkX89ABAMAoFHAROnnypFpaWtTS0iLp4wukW1padPjwYQUFBamgoEDFxcWqrKxUW1ubcnJyNH78eGVnZ0uSDMPQkiVLtGLFCu3cuVPNzc1atGiRpk+fbt1FNm3aNM2fP1+5ublqaGhQQ0ODcnNzlZmZqbi4OElSWlqa4uPj5Xa71dzcrJ07d2rlypXKzc21VnGys7PlcDiUk5OjtrY2VVZWqri4mDvGAACApPO4ff7111/X3XffbT0vLCyUJC1evFibN2/WqlWr1Nvbq7y8PHk8HiUlJam6uloTJkyw3rNhwwaFhIRo4cKF6u3t1dy5c7V582YFBwdbmS1btig/P9+6uywrK8vvt4uCg4O1bds25eXlafbs2QoLC1N2drZKS0utjGEYqqmp0bJlyzRjxgxFRkaqsLDQGjMAALC3IJOfWR5WT0+PDMOQ1+u9qq8XmrJ62zkzh9ZlXIaRXFwjOS6MPaPxn1UAV5eRfn/zt8YAAIBtUYQAAIBtUYQAAIBtBXyxNACMJWP1+joAI8OKEAAAsC1WhACMWdx1COBcWBECAAC2RRECAAC2RRECAAC2xTVCowDXOQAAcGmwIgQAAGyLFSH44TdVAAB2QhFCwChLAICxgiIE4KpD2QZwuVCEcMVwETjGEsobMDpRhABglKF0ARcPRQgAzoHVS2DsoggBGJUoJ5cHq08Y6/gdIQAAYFsUIQAAYFsUIQAAYFsUIQAAYFtcLA0AGFPsfIG3nY/9fFGEAOAqwt1wwOXFqTEAAGBbrAgBAK4KrIbhSqAI4ZLg/9AA++C6FIxmFCEAwCXHvxzhakURusL4PwfAPvjfO3D14WJpAABgW6wI2Qj/NgoAgD+KEAAAowD/MntpUIQAwKbs/MXKnW4YxDVCAADAtlgRAgDgCrPz6tyVRhECAOAsOH1mD7YoQk8//bSeeOIJdXZ26rOf/ayeeuop3XnnnVd6WACAUY6yNLzRMD9jvgi9/PLLKigo0NNPP63Zs2frZz/7me655x7t379fN95445UeHgBcEpxquXrw38XVLcg0TfNKD+JSSkpK0h133KFNmzZZr02bNk1f/epXVVJSMiTv8/nk8/ms516vVzfeeKPa29sVERFx0ceX8OgfLvpnAgBwIdoeS78onzOS77iLta8z9fT0KDY2VsePH5dhGJ8cNMcwn89nBgcHm6+88orf6/n5+eZdd9111vc8+uijpiQePHjw4MGDxxh4tLe3D9sVxvSpsffee08DAwOKiYnxez0mJkZdXV1nfU9RUZEKCwut56dPn9YHH3yg66+/XkFBQWd9z2DrvFSrRnbDfF58zOnFxXxefMzpxcV8SqZp6sSJE3K5XMPmxnQRGnRmgTFN8xNLjcPhkMPh8HvtU5/61Ij2ExERYdt/4C4F5vPiY04vLubz4mNOLy67z+ewp8T+15j+QcWoqCgFBwcPWf3p7u4eskoEAADsZ0wXodDQUCUmJqqmpsbv9ZqaGs2aNesKjQoAAFwtxvypscLCQrndbs2YMUPJycn6+c9/rsOHD+vBBx+8aPtwOBx69NFHh5xSw/lhPi8+5vTiYj4vPub04mI+R27M3z4vffyDiuvXr1dnZ6cSEhK0YcMG3XXXXVd6WAAA4AqzRRECAAA4mzF9jRAAAMBwKEIAAMC2KEIAAMC2KEIAAMC2KEIj9PTTT2vq1Km69tprlZiYqNdee23YvM/n0yOPPKKbbrpJDodDn/70p/Wf//mfl2m0V79A53PLli26/fbbNX78eE2cOFH/+q//qvfff/8yjfbqtmvXLi1YsEAul0tBQUH67W9/e8731NbWKjExUddee61uvvlmPfPMM5d+oKNIoHP6yiuvKDU1VTfccIMiIiKUnJysP/yBP6g86Hz+GR305z//WSEhIfrc5z53ycY32pzPfPKd9MkoQiPw8ssvq6CgQI888oiam5t155136p577tHhw4c/8T0LFy7Uzp079eyzz+rNN9/USy+9pFtvvfUyjvrqFeh81tXV6Vvf+paWLFmiffv26de//rUaGxv17W9/+zKP/Op06tQp3X777SovLx9R/uDBg/rKV76iO++8U83Nzfr+97+v/Px8bd269RKPdPQIdE537dql1NRUbd++XU1NTbr77ru1YMECNTc3X+KRjg6Bzucgr9erb33rW5o7d+4lGtnodD7zyXfSMC7CH3kf8774xS+aDz74oN9rt956q7l69eqz5nfs2GEahmG+//77l2N4o06g8/nEE0+YN998s99rP/nJT8zJkydfsjGOVpLMysrKYTOrVq0yb731Vr/Xli5das6cOfMSjmz0Gsmcnk18fLz52GOPXfwBjXKBzOe9995r/uAHPzAfffRR8/bbb7+k4xqtRjKffCcNjxWhc+jr61NTU5PS0tL8Xk9LS9Pu3bvP+p7f/e53mjFjhtavX69JkybpM5/5jFauXKne3t7LMeSr2vnM56xZs9TR0aHt27fLNE0dPXpUv/nNb5SRkXE5hjzm1NfXD5n/9PR0vf766+rv779CoxpbTp8+rRMnTui666670kMZtZ577jn97W9/06OPPnqlhzLq8Z00vDH/JzYu1HvvvaeBgYEhf6Q1JiZmyB9zHfTOO++orq5O1157rSorK/Xee+8pLy9PH3zwge3PyZ7PfM6aNUtbtmzRvffeqw8//FAfffSRsrKytHHjxssx5DGnq6vrrPP/0Ucf6b333tPEiROv0MjGjieffFKnTp3SwoULr/RQRqW3335bq1ev1muvvaaQEL6mLhTfScNjRWiEgoKC/J6bpjnktUGnT59WUFCQtmzZoi9+8Yv6yle+orKyMm3evJkG/r8Cmc/9+/crPz9fP/zhD9XU1KSqqiodPHjwov69OLs52/yf7XUE7qWXXtKaNWv08ssvKzo6+koPZ9QZGBhQdna2HnvsMX3mM5+50sMZE/hOGh5V+xyioqIUHBw8ZLWiu7t7yL9VD5o4caImTZokwzCs16ZNmybTNNXR0aFbbrnlko75anY+81lSUqLZs2fre9/7niTptttuU3h4uO6880796Ec/YgUjQE6n86zzHxISouuvv/4KjWpsePnll7VkyRL9+te/1rx58670cEalEydO6PXXX1dzc7MeeughSR9/kZumqZCQEFVXV+vLX/7yFR7l6MJ30vBYETqH0NBQJSYmqqamxu/1mpoazZo166zvmT17to4cOaKTJ09ar7311lu65pprNHny5Es63qvd+cznP/7xD11zjf8/qsHBwZL+/0oGRi45OXnI/FdXV2vGjBkaN27cFRrV6PfSSy8pJydHL774ItevXYCIiAi1traqpaXFejz44IOKi4tTS0uLkpKSrvQQRx2+k87hyl2nPXpUVFSY48aNM5999llz//79ZkFBgRkeHm4eOnTINE3TXL16tel2u638iRMnzMmTJ5tf//rXzX379pm1tbXmLbfcYn7729++UodwVQl0Pp977jkzJCTEfPrpp82//e1vZl1dnTljxgzzi1/84pU6hKvKiRMnzObmZrO5udmUZJaVlZnNzc3mu+++a5rm0Pl85513zPHjx5vf/e53zf3795vPPvusOW7cOPM3v/nNlTqEq06gc/riiy+aISEh5k9/+lOzs7PTehw/fvxKHcJVJdD5PBN3jfkLdD75ThoeRWiEfvrTn5o33XSTGRoaat5xxx1mbW2ttW3x4sVmSkqKX/7AgQPmvHnzzLCwMHPy5MlmYWGh+Y9//OMyj/rqFeh8/uQnPzHj4+PNsLAwc+LEieb9999vdnR0XOZRX53++Mc/mpKGPBYvXmya5tnn809/+pP5+c9/3gwNDTWnTJlibtq06fIP/CoW6JympKQMm7e78/ln9P+iCPk7n/nkO+mTBZkm5xYAAIA9cY0QAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwLYoQAACwrf8HVbKUddZUwtwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Restart\n",
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, weights = unitPop,bins = 50)\n",
    "plt.show()\n",
    "plt.hist([HDvPop[t] for t in popHDlist], bins=50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "27b51cd0-8bb6-4b16-bb79-37498e59ce5c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 2818 HDs with pop < 714497 to within 1618\n",
      "working on squaring up HD 16\n",
      "working on squaring up HD 123\n",
      "working on squaring up HD 191\n",
      "working on squaring up HD 242\n",
      "working on squaring up HD 307\n",
      "working on squaring up HD 358\n",
      "working on squaring up HD 408\n",
      "working on squaring up HD 458\n",
      "working on squaring up HD 508\n",
      "working on squaring up HD 558\n",
      "working on squaring up HD 608\n",
      "working on squaring up HD 658\n",
      "working on squaring up HD 745\n",
      "working on squaring up HD 795\n",
      "working on squaring up HD 847\n",
      "working on squaring up HD 901\n",
      "working on squaring up HD 953\n",
      "working on squaring up HD 1014\n",
      "working on squaring up HD 1067\n",
      "working on squaring up HD 1136\n",
      "working on squaring up HD 1192\n",
      "working on squaring up HD 1243\n",
      "working on squaring up HD 1295\n",
      "working on squaring up HD 1347\n",
      "working on squaring up HD 1397\n",
      "working on squaring up HD 1447\n",
      "working on squaring up HD 1497\n",
      "working on squaring up HD 1547\n",
      "working on squaring up HD 1597\n",
      "working on squaring up HD 1647\n",
      "working on squaring up HD 1697\n",
      "working on squaring up HD 1750\n",
      "working on squaring up HD 1801\n",
      "working on squaring up HD 1867\n",
      "working on squaring up HD 1918\n",
      "working on squaring up HD 1968\n",
      "working on squaring up HD 2018\n",
      "working on squaring up HD 2073\n",
      "working on squaring up HD 2124\n",
      "working on squaring up HD 2175\n",
      "working on squaring up HD 2234\n",
      "working on squaring up HD 2317\n",
      "working on squaring up HD 2367\n",
      "working on squaring up HD 2417\n",
      "working on squaring up HD 2467\n",
      "working on squaring up HD 2517\n",
      "working on squaring up HD 2567\n",
      "working on squaring up HD 2617\n",
      "working on squaring up HD 2668\n",
      "working on squaring up HD 2720\n",
      "working on squaring up HD 2771\n",
      "working on squaring up HD 2823\n",
      "working on squaring up HD 2876\n",
      "working on squaring up HD 2926\n",
      "working on squaring up HD 2977\n",
      "working on squaring up HD 3027\n",
      "working on squaring up HD 3077\n",
      "We have addressed underpop in a total of 2818 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList = list()\n",
    "minDistrictPop, maxDistrictPop = 0.99 * aDP, 1.01 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "\n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%50 == 0:\n",
    "        print(\"working on squaring up HD\",t)        \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "bc01409d-d9e4-43a6-9fae-c76aa7bdc855",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous unit avg and sd usage are 0.61986 0.17504\n",
      "amped unit avg and sd usage are 0.99972 0.15828\n"
     ]
    },
    {
     "data": {
      "image/png": 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xzSuivnO/+94zOLz5fTsoMDBQb7zxhubPn69hw4ZpyJAhWr16ta6//vouV+XGG2/U4MGD9d3vfld1dXX60Y9+pGXLlrW8/sQTT6h3795asWKFjhw5opiYGF199dV69NFHJUl9+/bV22+/rQULFig7O1ujR4/WU089pfvuu6/LdXOVAMMLbiZVVlYqOjpaFRUVioqKMrs6nfLXExX6/ovb9cd512lYYnSnywCALzt79qyOHj2q/v37Kyws7J8v+OneNPfcc49Onz5td5vFk7T530wd//2mZwQA4PlikjwiHKB7sOgZAAAwldNh5JNPPtHUqVOVkJCggICADnUdbd26VSkpKQoLC9OAAQP08ssvd6auAAD4ldzcXI++ReMqToeRmpoajRgxQr/+9a87VP7o0aOaMmWKUlNTtWfPHj366KOaP3++3n77bacrCwAAfI/TY0YmT56syZMnd7j8yy+/rL59+yorK0uSNHToUO3evVvPPfec3dK5AABI3rFQF5q54r9Vt48Z+fTTT5WWlmZzbNKkSdq9e7caGhpaPaeurk6VlZU2DwCA77NYLJJks2opPNuZM2ck2a4k66xun01z8uTJlvX3z4uLi9O5c+dUVlam+Ph4u3NWrFhhsyMhAMA/BAUFKTw8XN98842Cg4MVGMg8C09lGIbOnDmj0tJSxcTEtATJznDL1N5/3ZxH+meXzoXHz1u8eLEyMzNbnldWViopiSldAODrAgICFB8fr6NHj+rYsWNmVwcdEBMTo0suuaRL1+j2MHLJJZfo5MmTNsdKS0sVFBSk2NjWV7cLDQ1t2eAHAOBfQkJCNHjwYG7VeIHg4OAu9Yic1+1hZMyYMfrDH/5gc2zLli0aNWpUl+4vAQB8V2BgoN1qnvBdTt+Mq66uVmFhoQoLCyU1T90tLCxUUVGRpOZbLDNmzGgpP2fOHB07dkyZmZk6cOCA1q1bp7Vr12rhwoWu+QQAAMCrOd0zsnv3bk2YMKHl+fmxHTNnzlRubq5KSkpagokk9e/fX5s3b9aCBQv00ksvKSEhQatXr2ZaLwAAkNSJMHL99dc7nFPc2rbE48eP1+eff+7sWwEAAD/AnCkAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAEzVqTCSnZ2t/v37KywsTCkpKdq2bZvD8hs2bNCIESMUHh6u+Ph43XvvvSovL+9UhQEAgG9xOozk5eUpIyNDjz32mPbs2aPU1FRNnjxZRUVFrZbfvn27ZsyYofT0dO3bt09vvvmmdu3apVmzZnW58gAAwPs5HUZWrVql9PR0zZo1S0OHDlVWVpaSkpKUk5PTavnPPvtMl156qebPn6/+/fvruuuu0+zZs7V79+4uVx4AAHg/p8JIfX29CgoKlJaWZnM8LS1NO3fubPWcsWPH6vjx49q8ebMMw9DXX3+tt956SzfffHOb71NXV6fKykqbBwAA8E1OhZGysjI1NjYqLi7O5nhcXJxOnjzZ6jljx47Vhg0bNG3aNIWEhOiSSy5RTEyMXnzxxTbfZ8WKFYqOjm55JCUlOVNNAADgRTo1gDUgIMDmuWEYdsfO279/v+bPn69f/OIXKigo0HvvvaejR49qzpw5bV5/8eLFqqioaHkUFxd3ppoAAMALBDlTuFevXrJYLHa9IKWlpXa9JeetWLFC48aN06JFiyRJw4cPV0REhFJTU/Xkk08qPj7e7pzQ0FCFhoY6UzUAAOClnOoZCQkJUUpKivLz822O5+fna+zYsa2ec+bMGQUG2r6NxWKR1NyjAgAA/JvTt2kyMzP1m9/8RuvWrdOBAwe0YMECFRUVtdx2Wbx4sWbMmNFSfurUqXrnnXeUk5OjI0eOaMeOHZo/f75Gjx6thIQE130SAADglZy6TSNJ06ZNU3l5uR5//HGVlJRo2LBh2rx5s/r16ydJKikpsVlz5J577lFVVZV+/etf66GHHlJMTIxuuOEGPf300677FAAAwGs5HUYkae7cuZo7d26rr+Xm5todmzdvnubNm9eZtwIAAD6OvWkAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYKpO7U2D7nWotNrh6z0iQpQYY3VTbQAA6F6EEQ/SIyJE1mCLMvIKHZazBlv0wUPjCSQAAJ9AGPEgiTFWffDQeJ2qqW+zzKHSamXkFepUTT1hBADgEwgjHiYxxkrIAAD4FQawAgAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBU7E3jIidO17a7wR0AALBHGHGBE6drNXHlVtU2NDosZw22qEdEiJtqBQCAdyCMuMCpmnrVNjQqa9pVGtQ7ss1yPSJC2JEXAIALEEZcaFDvSA1LjDa7GgAAeBUGsAIAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAEzVqTCSnZ2t/v37KywsTCkpKdq2bZvD8nV1dXrsscfUr18/hYaGauDAgVq3bl2nKgwAAHxLkLMn5OXlKSMjQ9nZ2Ro3bpzWrFmjyZMna//+/erbt2+r59xxxx36+uuvtXbtWg0aNEilpaU6d+5clysPAAC8n9NhZNWqVUpPT9esWbMkSVlZWXr//feVk5OjFStW2JV/7733tHXrVh05ckQ9e/aUJF166aVdqzUAAPAZTt2mqa+vV0FBgdLS0myOp6WlaefOna2e8/vf/16jRo3SM888o8TERCUnJ2vhwoWqra1t833q6upUWVlp8wAAAL7JqZ6RsrIyNTY2Ki4uzuZ4XFycTp482eo5R44c0fbt2xUWFqZNmzaprKxMc+fO1bffftvmuJEVK1Zo+fLlzlQNAAB4qU4NYA0ICLB5bhiG3bHzmpqaFBAQoA0bNmj06NGaMmWKVq1apdzc3DZ7RxYvXqyKioqWR3FxcWeqCQAAvIBTPSO9evWSxWKx6wUpLS216y05Lz4+XomJiYqOjm45NnToUBmGoePHj2vw4MF254SGhio0NNSZqgEAAC/lVM9ISEiIUlJSlJ+fb3M8Pz9fY8eObfWccePG6auvvlJ1dXXLsYMHDyowMFB9+vTpRJUBAIAvcfo2TWZmpn7zm99o3bp1OnDggBYsWKCioiLNmTNHUvMtlhkzZrSUnz59umJjY3Xvvfdq//79+uSTT7Ro0SLdd999slqtrvskAADAKzk9tXfatGkqLy/X448/rpKSEg0bNkybN29Wv379JEklJSUqKipqKR8ZGan8/HzNmzdPo0aNUmxsrO644w49+eSTrvsUAADAazkdRiRp7ty5mjt3bquv5ebm2h277LLL7G7tAAAASOxNAwAATEYYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgKsIIAAAwFWEEAACYijACAABMRRgBAACmIowAAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqYLMrgA651BpdbtlekSEKDHG6obaAADQeYQRL9MjIkTWYIsy8grbLWsNtuiDh8YTSAAAHo0w4mUSY6z64KHxOlVT77DcodJqZeQV6lRNPWEEAODRCCNeKDHGSsAAAPgMBrACAABTEUYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYCrCCAAAMBVhBAAAmIowAgAATEUYAQAApiKMAAAAUxFGAACAqQgjAADAVIQRAABgqk6FkezsbPXv319hYWFKSUnRtm3bOnTejh07FBQUpKuuuqozbwsAAHyQ02EkLy9PGRkZeuyxx7Rnzx6lpqZq8uTJKioqcnheRUWFZsyYoRtvvLHTlQUAAL7H6TCyatUqpaena9asWRo6dKiysrKUlJSknJwch+fNnj1b06dP15gxYzpdWQAA4HucCiP19fUqKChQWlqazfG0tDTt3LmzzfPWr1+vw4cPa+nSpR16n7q6OlVWVto8AACAb3IqjJSVlamxsVFxcXE2x+Pi4nTy5MlWz/nyyy/1yCOPaMOGDQoKCurQ+6xYsULR0dEtj6SkJGeqCQAAvEinBrAGBATYPDcMw+6YJDU2Nmr69Olavny5kpOTO3z9xYsXq6KiouVRXFzcmWoCAAAv0LGuin/o1auXLBaLXS9IaWmpXW+JJFVVVWn37t3as2ePHnzwQUlSU1OTDMNQUFCQtmzZohtuuMHuvNDQUIWGhjpTNQAA4KWc6hkJCQlRSkqK8vPzbY7n5+dr7NixduWjoqK0d+9eFRYWtjzmzJmjIUOGqLCwUN/5zne6VnsAAOD1nOoZkaTMzEzdfffdGjVqlMaMGaNXXnlFRUVFmjNnjqTmWywnTpzQa6+9psDAQA0bNszm/N69eyssLMzuOAAA8E9Oh5Fp06apvLxcjz/+uEpKSjRs2DBt3rxZ/fr1kySVlJS0u+YIAADAeQGGYRhmV6I9lZWVio6OVkVFhaKiosyujp2/nqjQ91/crj/Ou07DEqPNro4kz6wTAMC/dPT32+meEQB+7HSxdKa8c+eGx0oxTNMHYI8wAqBjThdLL42WGs507vzgcOmBvxBIANghjADomDPlzUHktlelXh1fN0iSVHZQeuf+5msQRgBcgDACwDm9kqWEq8yuBQAf0qkVWAEAAFyFMAIAAEzFbRofd6i02uHrPSJClBhjdVNtAACwRxjpgBOna3Wqpr7N19v7wTdDj4gQWYMtysgrdFjOGmzRBw+NJ5AAAExDGGnHidO1mrhyq2obGh2WswZb1CMixE21al9ijFUfPDS+3RCVkVeoUzX1hBEAgGkII+04VVOv2oZGZU27SoN6R7ZZzhNvdyTGWD2uTgAAXIgw0kGDekf67LLqjCsBAJiJMOLHGFcCAPAEhBE/xrgSAIAnIIz4OcaVmKC9zebYUA6AnyGMAO7Ukc3m2FAOgJ8hjADu1N5mc67YUM5Rzwu9LgA8EGEEMEN3bTbXXs8LvS4APBBhBL7LH8dmOOp5cUWvCwB0A8IIfJO/j83orp4XAOgGhBH4JneMzQAAuARhBL6NHgIA8HiBZlcAAAD4N3pGAH9TdrDt13xxUC8Aj0cYAfxFeGzzoN137m+7jC8P6gXgsQgjgL+ISWoOGm1Nd2ZQLwCTEEYAfxKTRNAA4HEYwAoAAExFzwgA7+CPK+oCfoIwAsDzdXRF3Wn/KYX3sn+NoAJ4NMIIAM/X3oq6Z8qkvLul393e+vnMEgI8GmEEgPdwtKJuWzOFmCUEeDzCCADfwEwhwGsxmwYAAJiKMAIAAEzFbRrAE/nq/jG++rkAdAlhBPAkvrp/jK9+LgAuQRgBPImv7h/jCZ+LXhnAYxFGAE/jq7NCzPpc9MoAHo8wAsC3eUKvDACHCCMAfJ+v9jYBPoKpvQAAwFT0jADwHG0NMnU0+BSA1yOMADBfRweZhse6r04A3IYwAsB87Q0ylZh+C/gwwggAz8AgU8BvEUYAb8TYCgA+hDACeBPGVgDwQYQRwJswtgKADyKMwOucOF2rUzX1Dsv0rqlTbzfVx+0YW9E92LsGMA1hBF7lxOlaTVy5VbUNjQ7LpQQf09sWN1XK1/jbeBT2rgFMRxiBVzlVU6/ahkZlTbtKg3pHtlrmUGm1Xv2voxJhxDn+Oh6FvWsA0xFG0CGHSqsdvt4jIkSJMVY31UYa1DtSwxKj3fZ+fsGfx6Nw6wswFWEEDvWICJE12KKMvEKH5azBFn3w0Hi3BhJ0A36UAZigU2EkOztbzz77rEpKSnTFFVcoKytLqamprZZ95513lJOTo8LCQtXV1emKK67QsmXLNGnSpC5VHO6RGGPVBw+Ndzhg9FBptTLyCnWqpp4wAgBwmtNhJC8vTxkZGcrOzta4ceO0Zs0aTZ48Wfv371ffvn3tyn/yySe66aab9NRTTykmJkbr16/X1KlT9ec//1kjR450yYdA90qMsRIyAADdJtDZE1atWqX09HTNmjVLQ4cOVVZWlpKSkpSTk9Nq+aysLD388MO65pprNHjwYD311FMaPHiw/vCHP3S58gAAwPs5FUbq6+tVUFCgtLQ0m+NpaWnauXNnh67R1NSkqqoq9ezZs80ydXV1qqystHkAAADf5NRtmrKyMjU2NiouLs7meFxcnE6ePNmha6xcuVI1NTW644472iyzYsUKLV++3JmqAe51utg/Z50AQDfo1ADWgIAAm+eGYdgda83GjRu1bNky/fd//7d69257fczFixcrMzOz5XllZaWSkvhih4c4XSy9NFpqONN2GRbJ8j1tLfpG8AS6zKkw0qtXL1ksFrtekNLSUrvekgvl5eUpPT1db775piZOnOiwbGhoqEJDQ52pGuA+Z8qbg8htr0q9ku1fZ5Es39LeYnAET6DLnAojISEhSklJUX5+vm699daW4/n5+fr3f//3Ns/buHGj7rvvPm3cuFE333xz52sLeJJeyVLCVWbXAt3N0WJwBE/AJZy+TZOZmam7775bo0aN0pgxY/TKK6+oqKhIc+bMkdR8i+XEiRN67bXXJDUHkRkzZuiFF17Qtdde29KrYrVaFR3NCpoAvACLwQHdyukwMm3aNJWXl+vxxx9XSUmJhg0bps2bN6tfv36SpJKSEhUVFbWUX7Nmjc6dO6cHHnhADzzwQMvxmTNnKjc3t+ufAAAAeLVODWCdO3eu5s6d2+prFwaMjz/+uDNvAQAA/ITTi54BAAC4EhvlAd2ltamgbU0PBQA/RhgBXK0jU0HDY91bJwDwYIQRwNUcTQWVWCQLAC5AGAG6A1NBAaDDGMAKAABMRc8I0BpHG+ExCBUAXIowAlyooxvhMQgVAFyCMAJcqL2N8CQGoQKACxFGgLawER4AuAUDWAEAgKnoGQHc4MTpWp2qqXdYpkdEiBJjrG6qEQB4DsIIXOZQabXD1/31x/bE6VpNXLlVtQ2NDstZgy364KHxftlGAPwbYQRd1iMiRNZgizLyCh2W89cf21M19aptaFTWtKs0qHdkq2UOlVYrI69Qp2rq/a59fIKj6d4MdgbaRRhBlyXGWPXBQ+Md3obgx1Ya1DtSwxKjza4GXKm9fYik5tcf+AuBBHCAMAKXSIyx+m3IgB9rbx+isoPNQeVMOWEEcIAwAgBdwT5EQJcxtRcAAJiKnhF4lPamwLY3YwcA4H0II/AYzkyB7RER4qZaAQC6G2EEHqMjU2Al/12vBAB8FWEEHocpsADgXxjACgAATEXPCPxbaytnOlpNEwDgcoQReK/Txa0uNhVWVq1BASccn9veypnB4c1lAADdzu/DCFNJvdTpYuml0VLDGbuXBkl6IURqCrIqsK1A0d7Kmewnwk7DANzGr8MIU0n/oY0eBkme+6N8prw5iNz2qtQr2ealQ99U66dvFGrVnTdoiKO6s3Jmm9hpGIA7+XUYYSqpHPYwSHL5Jl+Oepo61QvVK1lKuMrm0FmjQvuMCjVEJjp/PUhip2EA7uXXYeQ8v55K6qCHwZWbfPWICJE12KKMvEKH5Xy+F8rL+PXfDQBuQxhBs1Z6GFwpMcaqDx4azxgEAIAdwgjcJjHGStAAANhh0TMAAGAqwggAADAVt2ngs9qbnePP41NYXweAJyGMwOc4M3PHH9fIYH0dAJ6GMAKf05GZO/68Roar19ehBwpAVxFG4JOYudO+rq4hQg8UAFchjADoFHqgALgKYQRAp9EDBcAVCCPwXI428Cs76N66AAC6DWEEnqm9Dfyk5k38wmPdVycAQLcgjMAzOdrA77zwWJftJuwpmJkCwB8RRuDZunkDP0/58XflzBQWNAPgbQgj8Eue9uPvqpkpLGgGwBsRRuCXnPnx33X0W51qY3Gw8pp6zfnPApf8+LtiZoqrFzQDAHcgjKB9jmauePG4jfZ+/J3pPfntfaMV6yBsuPLH31FPy/nXurqgGVzMR/8OAa5CGEHbwmObZ6y8c3/bZYLDpQf+4pNfph3pPZE8c1wJt2A8hJ//HQI6ijCCtsUkNX9JOlrr4537m1/30S9ST1rUy9PCETqAv0NAhxBG4FhMEl+SHsSTwhE6iL9DQLsIIwB8RnszmyR6jgBPRBiBudpa8p3l3uEkZ6Y1s4sw4FkII+i6zgaHM2VS3t1tL/nOcu9wQkemNbOLsAs52jtKYpYQnNKpMJKdna1nn31WJSUluuKKK5SVlaXU1NQ2y2/dulWZmZnat2+fEhIS9PDDD2vOnDmdrjQ8REdmCrQnOFz68dtSeK/Wr8+XGf6ho4vLuWJas6fd7ul0fS4IDKXVdaqsbWh53hjWUw2Rie1f5wIni75U79dSFXiuts0yTUFWffnDj+yu7+x7eZz2Qlh7+F5rldNhJC8vTxkZGcrOzta4ceO0Zs0aTZ48Wfv371ffvn3tyh89elRTpkzR/fffr9/97nfasWOH5s6dq4svvli33367Sz4ETNLeTIGO4C8m1P6PrSsXl+tIXdx+u8dB72JpdZ3m/2eBzp5rcniJsKBAPXrzUEVbgyVJQbXfqu8HP7EJDL3/8TjvjBGqOQ0ZKjei2rzOhSpqG/TG5g/0bGCtflo/V4cM+7AxKOCEXlC2MnM/0j6jf6vXSVCZ4oNrlHN3inpHhtoX8MTvho5s4NkeR1O5u6m36fzfr+DqE7Kc/bbVMpE94nRJ38FOX9tVnA4jq1atUnp6umbNmiVJysrK0vvvv6+cnBytWLHCrvzLL7+svn37KisrS5I0dOhQ7d69W8899xxhxBcwUwAd4GihNmeChqsWl2tv4biO3u5xtDpvRwRXh2hwkFWBDnoXe0t62yLJ0oELvmf7tDls/KwlbPxr0DgfVl4LeLrd61woJVBqtFg1d+bdrfZ8hJXtlTZl6+XvRaouxr6XKqj2W/XJ/5mCGmul19t4k3/8aJ9QL7ug6uhHtS1R1uDWQ8+FHP3gd2QDT0fOT+Uu+tQ+dLR321pqbpNp/9l6T3IbdT8frns0fK0PQhcpPKCu1VPPGKE6mb7DtEDiVBipr69XQUGBHnnkEZvjaWlp2rlzZ6vnfPrpp0pLS7M5NmnSJK1du1YNDQ0KDrZP33V1daqr+2eDVVRUSJIqKyudqW67qqsq1VR3RtVVlaqsDHDptb1GVbVUZzT/r4vbFwhqPKuQprOa/1rr3w/nhQUHKvtHI9UzvPV/jUtSTHiIEmLa+zFpUGVlQ5uvOlOfy2KDlHBR698LQY1BHbpOR1yiZYoJqHJcn6BAPf+jkbrYQRD7pqbe5haMJDWF9dDciPiW581t+M+wVp3wkVRr+6Pe2nUuFGUN1sW9LlF8TJ/WCzT2VGVjmKLfm9/mNaotYZpT+1P9eMLVSuxhGyBDK46oz7af6W8fvasnPqu36RXqGVClrOBshQc4vm3Vmo58wzVZwlQ8YbXOhfWwey204oj61Bk6XBWtuhDnx7MFN1yqgedCFbhxloP3XtPqewedPaWkP81X4NrbnKr7iVO1Sqr5Uo+ODtK5L85qf+rTqoseYHNeRfF+Xf3FUpUUH1F4TJzTn8uR87/bhmE4Lmg44cSJE4YkY8eOHTbHf/nLXxrJycmtnjN48GDjl7/8pc2xHTt2GJKMr776qtVzli5dakjiwYMHDx48ePjAo7i42GG+6NQA1oAA238tGIZhd6y98q0dP2/x4sXKzMxsed7U1KRvv/1WsbGxDt/nX1VWViopKUnFxcWKiopq/wQ/QJu0jnaxR5u0jnaxR5vYo03+yTAMVVVVKSEhwWE5p8JIr169ZLFYdPLkSZvjpaWliotrvWvnkksuabV8UFCQYmNb7+YKDQ1VaKhtd2xMTIwzVW0RFRXl938YLkSbtI52sUebtI52sUeb2KNNmkVHR7dbJtCZC4aEhCglJUX5+fk2x/Pz8zV27NhWzxkzZoxd+S1btmjUqFGtjhcBAAD+xakwIkmZmZn6zW9+o3Xr1unAgQNasGCBioqKWtYNWbx4sWbMmNFSfs6cOTp27JgyMzN14MABrVu3TmvXrtXChQtd9ykAAIDXcnrMyLRp01ReXq7HH39cJSUlGjZsmDZv3qx+/fpJkkpKSlRUVNRSvn///tq8ebMWLFigl156SQkJCVq9enW3T+sNDQ3V0qVL7W73+DPapHW0iz3apHW0iz3axB5t4rwAw2hvvg0AAED3cfo2DQAAgCsRRgAAgKkIIwAAwFSEEQAAYCqvDiPZ2dnq37+/wsLClJKSom3btnXovB07digoKEhXXXVV91bQBM62SV1dnR577DH169dPoaGhGjhwoNatW+em2rqPs+2yYcMGjRgxQuHh4YqPj9e9996r8vIu7E7sYT755BNNnTpVCQkJCggI0LvvvtvuOVu3blVKSorCwsI0YMAAvfzyy91fUTdytk3eeecd3XTTTbr44osVFRWlMWPG6P3333dPZd2oM39WzvPV79rOtIm/fNd2lteGkby8PGVkZOixxx7Tnj17lJqaqsmTJ9tMK25NRUWFZsyYoRtvvNFNNXWfzrTJHXfcoQ8//FBr167V3/72N23cuFGXXXaZG2vd/Zxtl+3bt2vGjBlKT0/Xvn379Oabb2rXrl0tO1X7gpqaGo0YMUK//vWvO1T+6NGjmjJlilJTU7Vnzx49+uijmj9/vt5+++1urqn7ONsmn3zyiW666SZt3rxZBQUFmjBhgqZOnao9e/Z0c03dy9l2Oc+Xv2s70yb+8F3bJR3bIs/zjB492pgzZ47Nscsuu8x45JFHHJ43bdo0Y8mSJcbSpUuNESNGdGMN3c/ZNvnf//1fIzo62igvL3dH9UzjbLs8++yzxoABA2yOrV692ujTp0+31dFMkoxNmzY5LPPwww8bl112mc2x2bNnG9dee2031sw8HWmT1lx++eXG8uXLXV8hD+FMu/jyd+2/6kib+Mt3bVd4Zc9IfX29CgoKlJaWZnM8LS1NO3e2vaX3+vXrdfjwYS1durS7q+h2nWmT3//+9xo1apSeeeYZJSYmKjk5WQsXLlRtba07quwWnWmXsWPH6vjx49q8ebMMw9DXX3+tt956SzfffLM7quyRPv30U7s2nDRpknbv3q2GBsfbzfuLpqYmVVVVqWfPnmZXxXS+/F3bGf7wXdtVndq112xlZWVqbGy025wvLi7OblO+87788ks98sgj2rZtm4KCvPJjO9SZNjly5Ii2b9+usLAwbdq0SWVlZZo7d66+/fZbn7mX2Zl2GTt2rDZs2KBp06bp7NmzOnfunP7t3/5NL774ojuq7JFOnjzZahueO3dOZWVlio+PN6lmnmPlypWqqanRHXfcYXZVTOXr37Wd4Q/ftV3llT0j5wUEBNg8NwzD7pgkNTY2avr06Vq+fLmSk5PdVT1TdLRNpOZ/yQUEBGjDhg0aPXq0pkyZolWrVik3N9fnErsz7bJ//37Nnz9fv/jFL1RQUKD33ntPR48ebdl/yV+11oatHfdHGzdu1LJly5SXl6fevXubXR3T+NN3rTP86bu2s7wytvbq1UsWi8XuX7alpaV2/3qTpKqqKu3evVt79uzRgw8+KKn5D4dhGAoKCtKWLVt0ww03uKXu3cXZNpGk+Ph4JSYm2mzvPHToUBmGoePHj2vw4MHdWmd36Ey7rFixQuPGjdOiRYskScOHD1dERIRSU1P15JNP+mUvwCWXXNJqGwYFBSk2NtakWnmGvLw8paen680339TEiRPNro6p/OG7tjP84bu2q7yyZyQkJEQpKSnKz8+3OZ6fn6+xY8falY+KitLevXtVWFjY8pgzZ46GDBmiwsJCfec733FX1buNs20iSePGjdNXX32l6urqlmMHDx5UYGCg+vTp0631dZfOtMuZM2cUGGj7V8NisUj6Z2+AvxkzZoxdG27ZskWjRo1ScHCwSbUy38aNG3XPPffo9ddf9+sxRef5w3dtZ/jDd22XmTVytqveeOMNIzg42Fi7dq2xf/9+IyMjw4iIiDD+/ve/G4ZhGI888ohx9913t3m+L47wdrZNqqqqjD59+hg/+MEPjH379hlbt241Bg8ebMyaNcusj9AtnG2X9evXG0FBQUZ2drZx+PBhY/v27caoUaOM0aNHm/URXK6qqsrYs2ePsWfPHkOSsWrVKmPPnj3GsWPHDMOwb5MjR44Y4eHhxoIFC4z9+/cba9euNYKDg4233nrLrI/gcs62yeuvv24EBQUZL730klFSUtLyOH36tFkfoVs42y4X8sXvWmfbxF++a7vCa8OIYRjGSy+9ZPTr188ICQkxrr76amPr1q0tr82cOdMYP358m+f64l8Qw3C+TQ4cOGBMnDjRsFqtRp8+fYzMzEzjzJkzbq5193O2XVavXm1cfvnlhtVqNeLj44277rrLOH78uJtr3X3+9Kc/GZLsHjNnzjQMo/U2+fjjj42RI0caISEhxqWXXmrk5OS4v+LdyNk2GT9+vMPyvqIzf1b+lS9+13amTfzlu7azAgzDT/udAQCAR/DKMSMAAMB3EEYAAICpCCMAAMBUhBEAAGAqwggAADAVYQQAAJiKMAIAAExFGAEAAKYijAAAAFMRRgAAgKkIIwAAwFSEEQAAYKr/ByOr4+n1pu/aAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prevUnitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "46dc9be4-4cd6-4d82-ba39-aa4af6ad4bb1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#CONSIDER MAKING A METHOD OUT OF THE PATCH-BUILD ROUTINE -- WHAT DO WE NEED TO PASS?\n",
    "plt.hist([ampedHDpop[t] for t in popHDlist],bins=50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "dd7d9818-344c-4150-917b-57a4ee051c92",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 20 overPopped HDs to within 1618\n",
      "working on squaring down HD 23\n",
      "We have addressed underpop in a total of 2818 HDs\n",
      "We have addressed overpop in a total of 20 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))   \n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    if ii%30 == 0:\n",
    "        print(\"working on squaring down HD\",t)\n",
    "    #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "    excess = HDvPop[t] - aDP\n",
    "    origExcess = excess\n",
    "    HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "    starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "    barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)\n",
    "\n",
    "    for u in set(HDunitList[t]).difference(barredSet):\n",
    "        isBoundary = False\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t]:\n",
    "                isBoundary = True\n",
    "                break\n",
    "        if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "            HDboundaryList.append(u)\n",
    "            HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "    currList = HDunitList[t].copy()\n",
    "    shedList, stillGoing = list(), True\n",
    "    while excess > maxGap and len(HDboundaryList) > 0:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "        while i < len(HDboundaryScore) and notYetPicked:        \n",
    "            listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "            unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "            tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "            unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "            if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #add this eligible unit\n",
    "            shedList.append(unitNoToShed)\n",
    "            excess -= unitPop[unitNoToShed]        \n",
    "            del currList[currList.index(unitNoToShed) ]\n",
    "            del HDboundaryList[listNo]\n",
    "            del HDboundaryScore[listNo]\n",
    "            for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                  u not in barredSet): \n",
    "                    HDboundaryList.append(u)\n",
    "                    HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "            for uu in HDboundaryList.copy():\n",
    "                if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                    del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                    del HDboundaryList[HDboundaryList.index(uu)]                \n",
    "    for u in shedList:\n",
    "        unitUse[u] -= HDweight[t] * nDistricts\n",
    "    HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "             np.sum([unitPop[u] for u in shedList]) )\n",
    "    \n",
    "    HDnShedUnits[t] = -1 * len(shedList)\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "9a19b23e-43cc-4609-9ee7-6d1057a7a9e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the stats prior to any equi-pop patching\n",
      "orig unit avg and sd usage are 0.61986 0.17504\n",
      "amped unit avg and sd usage are 0.99972 0.15828\n",
      "shed unit avg and sd usage are 0.99903 0.15874\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here are the final populations\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 3108\n",
      "working on HD 300 out of 3108\n",
      "working on HD 600 out of 3108\n",
      "working on HD 900 out of 3108\n",
      "working on HD 1200 out of 3108\n",
      "working on HD 1500 out of 3108\n",
      "working on HD 1800 out of 3108\n",
      "working on HD 2100 out of 3108\n",
      "working on HD 2400 out of 3108\n",
      "working on HD 2700 out of 3108\n",
      "working on HD 3000 out of 3108\n",
      "all done checking HD and complement contiguity for all 3108 HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"Here are the stats prior to any equi-pop patching\")\n",
    "shedUnitUse = [0. for u in range(nUnits)]\n",
    "shedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "shedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in shedHDlist[t]:\n",
    "        shedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(latestUnitUse,bins=50,weights=unitPop,label=\"pre-squaring\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.hist(shedUnitUse, bins=50, weights=unitPop,label=\"shed\",histtype=\"step\")\n",
    "plt.legend()\n",
    "shedUnitUseAvg, shedUnitUseSD = getWeightedAvgAndSD(shedUnitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "print(\"shed unit avg and sd usage are\", r5(shedUnitUseAvg),  r5(shedUnitUseSD) )\n",
    "plt.show()\n",
    "# note: when I ran this early Jan, went from 0.12662 to 0.09961 to 0.09432 SD orig-amped-shed, but contig not yet done\n",
    "print(\"and here are the final populations\")\n",
    "plt.hist([shedHDpop[t] for t in popHDlist],bins=20)\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "c0c3a3d8-cf79-40ad-aa2e-b6793266f1d4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    }
   ],
   "source": [
    "print(\"prior to patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        for i,uu in enumerate(surrounders):\n",
    "            if u == uu:\n",
    "                unitVTDlist[u].append(surroundedVTDs[i])\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        vtdList[t] += unitVTDlist[u]\n",
    "    #add more stuff here to convert to vtd lists\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"unpatchedFromCluster.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "1b794580-5a58-4238-b310-7c87872ed679",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing vtdlist for patching\n",
      "Must have already established unitGeoms, pops, topology\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched vtdlist, e.g. ./2024state_HD_output/CO3108contigUnpatchedB.csv ./2024state_HD_output/CO3108contigPatchUpBetter.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I read in 3108 HD lists of vtds\n",
      "working on converting HD 0 from vtd list to unit list\n",
      "working on converting HD 500 from vtd list to unit list\n",
      "working on converting HD 1000 from vtd list to unit list\n",
      "working on converting HD 1500 from vtd list to unit list\n",
      "working on converting HD 2000 from vtd list to unit list\n",
      "working on converting HD 2500 from vtd list to unit list\n",
      "working on converting HD 3000 from vtd list to unit list\n",
      "orig unit avg and sd usage are 0.99963 0.09004\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology\")\n",
    "infile = input(\"enter the unpatched vtdlist, e.g. ./2024state_HD_output/CO3108contigUnpatchedB.csv\")\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of vtds\")\n",
    "HDunitList = [list() for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if t%500 == 0:\n",
    "        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "    for v in inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "        if v in allUnits:\n",
    "            HDunitList[t].append(allUnits.index(v))\n",
    "    for c in unitCounties:\n",
    "        if countyTractList[c][0] in inVTDlist[t]:\n",
    "            u = allUnits.index(c+0.5)\n",
    "            HDunitList[t].append(u)\n",
    "    for j, L in enumerate(CCBlist):\n",
    "        c = L[0]\n",
    "        if countyTractList[c][0] in inVTDlist[t]:\n",
    "            u = allUnits.index(j+0.25)\n",
    "            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5f3a5392-11f1-4061-a458-aecd834b2748",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing avg dist from a unit to its HD centerpoint for each HD\n",
      "working on HD 0\n",
      "working on HD 500\n",
      "working on HD 1000\n",
      "working on HD 1500\n",
      "working on HD 2000\n",
      "working on HD 2500\n",
      "working on HD 3000\n",
      "all avgDist to HD centers computed\n"
     ]
    }
   ],
   "source": [
    "#needed for restart only  about 5sec per 2000 HDs\n",
    "print(\"computing avg dist from a unit to its HD centerpoint for each HD\")\n",
    "avgDist = [0. for t in range(nHDs)]\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    if HDvPop[t] > 0.1 * aDP:\n",
    "        avgDist[t] = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        popHDlist.append(t)\n",
    "print(\"all avgDist to HD centers computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ea0db02f-9df8-4906-acb4-086c29c0fcc1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets confirm no discontig problems with these HDunitLists\n",
      "working on HD 0\n",
      "working on HD 300\n",
      "working on HD 600\n",
      "working on HD 900\n",
      "working on HD 1200\n",
      "working on HD 1500\n",
      "working on HD 1800\n",
      "working on HD 2100\n",
      "working on HD 2400\n",
      "working on HD 2700\n",
      "working on HD 3000\n",
      "out of 3097 total HDs, there were 3097 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "print(\"Lets confirm no discontig problems with these HDunitLists\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "27b42f93-dc87-4afe-8eb3-f30fdff4a737",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2820 1.052626279999999 44650.0\n",
      "2821 1.0292615759999992 65547.0\n",
      "2822 0.9434251760000004 105949.0\n",
      "2823 0.980673688 42401.0\n"
     ]
    }
   ],
   "source": [
    "for j in range(len(CCBlist)):\n",
    "    u = allUnits.index(j+0.25)\n",
    "    print(u,unitUse[u], unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "72941b8f-7be6-4a31-9377-618f44a34336",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unpatchedUnitUse = unitUse.copy()              #... for safekeeping\n",
    "unpatchedHDlist =  [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "unpatchedHDpop =   HDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "5f9ca091-1eb6-4135-a233-7f5ae0f5e3d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unitUse = unpatchedUnitUse.copy()              #... restarting\n",
    "HDunitList =  [unpatchedHDlist[t].copy() for t in range(nHDs) ]\n",
    "HDvPop =   unpatchedHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e9dd457d-fb37-49cf-9b19-19c17c328ede",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used\n",
      "this block is a WIP - let's further tighten the distro with exchanges up to 36085\n",
      "current avg and SD of unit usage are 0.99903 0.15874 . Now trying to increase up to 56 units' underusage\n",
      "starting to increase usage for unit 2027 with usage 0.61358 . Total UU units tried = 1\n",
      "try to add unit 2027 from 0 th HD.  Usage up to 0.613576224\n",
      "try to add unit 2027 from 20 th HD.  Usage up to 0.6715893759999999\n",
      "try to add unit 2027 from 40 th HD.  Usage up to 0.7221232959999999\n",
      "all done trying to reduce usage of unit 2027 final usage = 0.74022 26 sec elapsed 46 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 0.99913 0.15585\n",
      "starting to increase usage for unit 2071 with usage 0.62857 . Total UU units tried = 2\n",
      "try to add unit 2071 from 0 th HD.  Usage up to 0.62857076\n",
      "try to add unit 2071 from 20 th HD.  Usage up to 0.677742592\n",
      "try to add unit 2071 from 40 th HD.  Usage up to 0.727152784\n",
      "all done trying to reduce usage of unit 2071 final usage = 0.73886 64 sec elapsed 38 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99914 0.15382\n",
      "starting to increase usage for unit 2025 with usage 0.63109 . Total UU units tried = 3\n",
      "try to add unit 2025 from 0 th HD.  Usage up to 0.631089952\n",
      "try to add unit 2025 from 20 th HD.  Usage up to 0.6862487839999999\n",
      "all done trying to reduce usage of unit 2025 final usage = 0.72902 99 sec elapsed 34 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99914 0.15258\n",
      "starting to increase usage for unit 2064 with usage 0.63803 . Total UU units tried = 4\n",
      "try to add unit 2064 from 0 th HD.  Usage up to 0.63803452\n",
      "try to add unit 2064 from 20 th HD.  Usage up to 0.6866824720000001\n",
      "try to add unit 2064 from 40 th HD.  Usage up to 0.7403190160000002\n",
      "all done trying to reduce usage of unit 2064 final usage = 0.754 146 sec elapsed 43 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99914 0.15122\n",
      "starting to increase usage for unit 2076 with usage 0.64062 . Total UU units tried = 5\n",
      "try to add unit 2076 from 0 th HD.  Usage up to 0.6406181039999997\n",
      "try to add unit 2076 from 20 th HD.  Usage up to 0.6875217039999998\n",
      "try to add unit 2076 from 40 th HD.  Usage up to 0.731196952\n",
      "all done trying to reduce usage of unit 2076 final usage = 0.76125 185 sec elapsed 46 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99915 0.14956\n",
      "starting to increase usage for unit 2055 with usage 0.64367 . Total UU units tried = 6\n",
      "try to add unit 2055 from 0 th HD.  Usage up to 0.6436689120000002\n",
      "try to add unit 2055 from 20 th HD.  Usage up to 0.6859946240000001\n",
      "try to add unit 2055 from 40 th HD.  Usage up to 0.7373315599999998\n",
      "try to add unit 2055 from 60 th HD.  Usage up to 0.7704111120000001\n",
      "try to add unit 2055 from 80 th HD.  Usage up to 0.8135958640000003\n",
      "try to add unit 2055 from 100 th HD.  Usage up to 0.8755984400000004\n",
      "try to add unit 2055 from 120 th HD.  Usage up to 0.9371439360000006\n",
      "all done trying to reduce usage of unit 2055 final usage = 0.94403 283 sec elapsed 116 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 0.99919 0.14564\n",
      "starting to increase usage for unit 2053 with usage 0.6523 . Total UU units tried = 7\n",
      "try to add unit 2053 from 0 th HD.  Usage up to 0.6522997119999998\n",
      "try to add unit 2053 from 20 th HD.  Usage up to 0.7051947359999996\n",
      "try to add unit 2053 from 40 th HD.  Usage up to 0.7532297119999997\n",
      "try to add unit 2053 from 60 th HD.  Usage up to 0.7918351279999997\n",
      "try to add unit 2053 from 80 th HD.  Usage up to 0.850095088\n",
      "try to add unit 2053 from 100 th HD.  Usage up to 0.9119646480000001\n",
      "all done trying to reduce usage of unit 2053 final usage = 0.95082 402 sec elapsed 108 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 0.99919 0.14336\n",
      "starting to increase usage for unit 2056 with usage 0.66143 . Total UU units tried = 8\n",
      "try to add unit 2056 from 0 th HD.  Usage up to 0.6614268959999999\n",
      "try to add unit 2056 from 20 th HD.  Usage up to 0.7137294159999998\n",
      "try to add unit 2056 from 40 th HD.  Usage up to 0.746104168\n",
      "try to add unit 2056 from 60 th HD.  Usage up to 0.7916403120000001\n",
      "try to add unit 2056 from 80 th HD.  Usage up to 0.8405849440000001\n",
      "try to add unit 2056 from 100 th HD.  Usage up to 0.9090306480000003\n",
      "all done trying to reduce usage of unit 2056 final usage = 0.93101 535 sec elapsed 96 0 successful, failed patches, couldn't start= 12\n",
      "current avg and SD of usage are 0.99919 0.14128\n",
      "starting to increase usage for unit 18 with usage 0.63602 . Total UU units tried = 9\n",
      "try to add unit 18 from 0 th HD.  Usage up to 0.6360191039999997\n",
      "try to add unit 18 from 20 th HD.  Usage up to 0.6727719679999996\n",
      "try to add unit 18 from 40 th HD.  Usage up to 0.7025782639999996\n",
      "try to add unit 18 from 60 th HD.  Usage up to 0.7227903279999996\n",
      "try to add unit 18 from 80 th HD.  Usage up to 0.7542892719999997\n",
      "try to add unit 18 from 100 th HD.  Usage up to 0.7993347759999997\n",
      "try to add unit 18 from 120 th HD.  Usage up to 0.8441757679999998\n",
      "try to add unit 18 from 140 th HD.  Usage up to 0.9017843599999997\n",
      "try to add unit 18 from 160 th HD.  Usage up to 0.9459264159999998\n",
      "all done trying to reduce usage of unit 18 final usage = 0.95039 670 sec elapsed 135 0 successful, failed patches, couldn't start= 27\n",
      "current avg and SD of usage are 0.99927 0.13636\n",
      "starting to increase usage for unit 2049 with usage 0.68461 . Total UU units tried = 10\n",
      "try to add unit 2049 from 0 th HD.  Usage up to 0.6846119360000001\n",
      "try to add unit 2049 from 20 th HD.  Usage up to 0.7358491680000003\n",
      "try to add unit 2049 from 40 th HD.  Usage up to 0.7816276720000004\n",
      "try to add unit 2049 from 60 th HD.  Usage up to 0.8182025360000005\n",
      "try to add unit 2049 from 80 th HD.  Usage up to 0.8520934240000005\n",
      "try to add unit 2049 from 100 th HD.  Usage up to 0.8896416080000006\n",
      "try to add unit 2049 from 120 th HD.  Usage up to 0.9381414400000009\n",
      "all done trying to reduce usage of unit 2049 final usage = 0.94105 869 sec elapsed 113 1 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 0.99927 0.13417\n",
      "starting to increase usage for unit 2054 with usage 0.69603 . Total UU units tried = 11\n",
      "try to add unit 2054 from 0 th HD.  Usage up to 0.6960250640000001\n",
      "try to add unit 2054 from 20 th HD.  Usage up to 0.7393635519999999\n",
      "try to add unit 2054 from 40 th HD.  Usage up to 0.7816683920000002\n",
      "try to add unit 2054 from 60 th HD.  Usage up to 0.8154241360000001\n",
      "try to add unit 2054 from 80 th HD.  Usage up to 0.8274441280000001\n",
      "try to add unit 2054 from 100 th HD.  Usage up to 0.8360510400000002\n",
      "try to add unit 2054 from 120 th HD.  Usage up to 0.8519770160000003\n",
      "try to add unit 2054 from 140 th HD.  Usage up to 0.8720583680000003\n",
      "try to add unit 2054 from 160 th HD.  Usage up to 0.8857868560000002\n",
      "try to add unit 2054 from 180 th HD.  Usage up to 0.9088624960000004\n",
      "try to add unit 2054 from 200 th HD.  Usage up to 0.9340899200000004\n",
      "all done trying to reduce usage of unit 2054 final usage = 0.95096 964 sec elapsed 72 0 successful, failed patches, couldn't start= 141\n",
      "current avg and SD of usage are 0.99929 0.13196\n",
      "starting to increase usage for unit 870 with usage 0.69957 . Total UU units tried = 12\n",
      "try to add unit 870 from 0 th HD.  Usage up to 0.6995671360000002\n",
      "try to add unit 870 from 20 th HD.  Usage up to 0.7441775840000001\n",
      "try to add unit 870 from 40 th HD.  Usage up to 0.7874618160000001\n",
      "try to add unit 870 from 60 th HD.  Usage up to 0.8263704080000001\n",
      "try to add unit 870 from 80 th HD.  Usage up to 0.8625918640000001\n",
      "try to add unit 870 from 100 th HD.  Usage up to 0.8964683840000002\n",
      "try to add unit 870 from 120 th HD.  Usage up to 0.9164529200000002\n",
      "all done trying to reduce usage of unit 870 final usage = 0.95189 1083 sec elapsed 113 1 successful, failed patches, couldn't start= 25\n",
      "current avg and SD of usage are 0.99937 0.12782\n",
      "starting to increase usage for unit 12 with usage 0.71574 . Total UU units tried = 13\n",
      "try to add unit 12 from 0 th HD.  Usage up to 0.715743208\n",
      "try to add unit 12 from 20 th HD.  Usage up to 0.7630126959999999\n",
      "try to add unit 12 from 40 th HD.  Usage up to 0.7981076479999999\n",
      "try to add unit 12 from 60 th HD.  Usage up to 0.8425752480000002\n",
      "try to add unit 12 from 80 th HD.  Usage up to 0.8863615359999999\n",
      "try to add unit 12 from 100 th HD.  Usage up to 0.9388014639999998\n",
      "all done trying to reduce usage of unit 12 final usage = 0.95386 1209 sec elapsed 104 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 0.99939 0.12621\n",
      "starting to increase usage for unit 887 with usage 0.72083 . Total UU units tried = 14\n",
      "try to add unit 887 from 0 th HD.  Usage up to 0.7208270800000002\n",
      "try to add unit 887 from 20 th HD.  Usage up to 0.7524282240000002\n",
      "try to add unit 887 from 40 th HD.  Usage up to 0.7970141280000003\n",
      "try to add unit 887 from 60 th HD.  Usage up to 0.83549936\n",
      "try to add unit 887 from 80 th HD.  Usage up to 0.8642018560000001\n",
      "try to add unit 887 from 100 th HD.  Usage up to 0.9006842080000002\n",
      "try to add unit 887 from 120 th HD.  Usage up to 0.9289018160000001\n",
      "all done trying to reduce usage of unit 887 final usage = 0.95115 1414 sec elapsed 117 2 successful, failed patches, couldn't start= 12\n",
      "current avg and SD of usage are 0.99944 0.12379\n",
      "starting to increase usage for unit 2105 with usage 0.72217 . Total UU units tried = 15\n",
      "try to add unit 2105 from 0 th HD.  Usage up to 0.7221749679999999\n",
      "try to add unit 2105 from 20 th HD.  Usage up to 0.7734972240000001\n",
      "try to add unit 2105 from 40 th HD.  Usage up to 0.8251617040000001\n",
      "try to add unit 2105 from 60 th HD.  Usage up to 0.8710433040000002\n",
      "try to add unit 2105 from 80 th HD.  Usage up to 0.9195941200000004\n",
      "all done trying to reduce usage of unit 2105 final usage = 0.95163 1579 sec elapsed 91 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99944 0.12231\n",
      "starting to increase usage for unit 2057 with usage 0.73466 . Total UU units tried = 16\n",
      "try to add unit 2057 from 0 th HD.  Usage up to 0.7346556000000003\n",
      "try to add unit 2057 from 20 th HD.  Usage up to 0.7878778640000001\n",
      "try to add unit 2057 from 40 th HD.  Usage up to 0.8423380000000004\n",
      "try to add unit 2057 from 60 th HD.  Usage up to 0.8855113120000002\n",
      "try to add unit 2057 from 80 th HD.  Usage up to 0.9229656240000002\n",
      "all done trying to reduce usage of unit 2057 final usage = 0.95263 1746 sec elapsed 84 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99944 0.12093\n",
      "starting to increase usage for unit 25 with usage 0.73593 . Total UU units tried = 17\n",
      "try to add unit 25 from 0 th HD.  Usage up to 0.7359269839999999\n",
      "try to add unit 25 from 20 th HD.  Usage up to 0.799433952\n",
      "try to add unit 25 from 40 th HD.  Usage up to 0.857949856\n",
      "try to add unit 25 from 60 th HD.  Usage up to 0.89352612\n",
      "try to add unit 25 from 80 th HD.  Usage up to 0.9259106880000001\n",
      "all done trying to reduce usage of unit 25 final usage = 0.95331 1923 sec elapsed 93 2 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99944 0.11978\n",
      "starting to increase usage for unit 2073 with usage 0.73299 . Total UU units tried = 18\n",
      "try to add unit 2073 from 0 th HD.  Usage up to 0.7329912000000003\n",
      "try to add unit 2073 from 20 th HD.  Usage up to 0.787369128\n",
      "try to add unit 2073 from 40 th HD.  Usage up to 0.8368411360000001\n",
      "try to add unit 2073 from 60 th HD.  Usage up to 0.8826112960000001\n",
      "try to add unit 2073 from 80 th HD.  Usage up to 0.9229114239999999\n",
      "all done trying to reduce usage of unit 2073 final usage = 0.9516 2104 sec elapsed 81 2 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99944 0.1187\n",
      "starting to increase usage for unit 29 with usage 0.73718 . Total UU units tried = 19\n",
      "try to add unit 29 from 0 th HD.  Usage up to 0.7371797519999995\n",
      "try to add unit 29 from 20 th HD.  Usage up to 0.7794112399999993\n",
      "try to add unit 29 from 40 th HD.  Usage up to 0.8345462959999994\n",
      "try to add unit 29 from 60 th HD.  Usage up to 0.8796360799999994\n",
      "try to add unit 29 from 80 th HD.  Usage up to 0.9045673599999994\n",
      "try to add unit 29 from 100 th HD.  Usage up to 0.9304131119999993\n",
      "all done trying to reduce usage of unit 29 final usage = 0.956 2248 sec elapsed 73 1 successful, failed patches, couldn't start= 34\n",
      "current avg and SD of usage are 0.99943 0.11745\n",
      "starting to increase usage for unit 532 with usage 0.74463 . Total UU units tried = 20\n",
      "try to add unit 532 from 0 th HD.  Usage up to 0.744633256\n",
      "try to add unit 532 from 20 th HD.  Usage up to 0.7718257119999999\n",
      "try to add unit 532 from 40 th HD.  Usage up to 0.80490484\n",
      "try to add unit 532 from 60 th HD.  Usage up to 0.8439699839999999\n",
      "try to add unit 532 from 80 th HD.  Usage up to 0.8829793599999998\n",
      "try to add unit 532 from 100 th HD.  Usage up to 0.9054421599999998\n",
      "all done trying to reduce usage of unit 532 final usage = 0.93206 2373 sec elapsed 111 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99944 0.1158\n",
      "starting to increase usage for unit 637 with usage 0.74919 . Total UU units tried = 21\n",
      "try to add unit 637 from 0 th HD.  Usage up to 0.7491942399999999\n",
      "try to add unit 637 from 20 th HD.  Usage up to 0.785239064\n",
      "all done trying to reduce usage of unit 637 final usage = 0.79514 2404 sec elapsed 21 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 0.99945 0.11527\n",
      "starting to increase usage for unit 2700 with usage 0.74949 . Total UU units tried = 22\n",
      "try to add unit 2700 from 0 th HD.  Usage up to 0.7494920319999997\n",
      "try to add unit 2700 from 20 th HD.  Usage up to 0.7840902639999997\n",
      "try to add unit 2700 from 40 th HD.  Usage up to 0.8436249199999999\n",
      "try to add unit 2700 from 60 th HD.  Usage up to 0.9066138319999998\n",
      "all done trying to reduce usage of unit 2700 final usage = 0.95056 2551 sec elapsed 74 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99946 0.1141\n",
      "starting to increase usage for unit 534 with usage 0.75115 . Total UU units tried = 23\n",
      "try to add unit 534 from 0 th HD.  Usage up to 0.7511482880000002\n",
      "try to add unit 534 from 20 th HD.  Usage up to 0.7799459440000003\n",
      "try to add unit 534 from 40 th HD.  Usage up to 0.8142651360000003\n",
      "try to add unit 534 from 60 th HD.  Usage up to 0.8402716400000002\n",
      "try to add unit 534 from 80 th HD.  Usage up to 0.886066176\n",
      "try to add unit 534 from 100 th HD.  Usage up to 0.9073746399999999\n",
      "try to add unit 534 from 120 th HD.  Usage up to 0.9346946560000001\n",
      "all done trying to reduce usage of unit 534 final usage = 0.93994 2759 sec elapsed 114 3 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99946 0.11292\n",
      "starting to increase usage for unit 621 with usage 0.75258 . Total UU units tried = 24\n",
      "try to add unit 621 from 0 th HD.  Usage up to 0.752582088\n",
      "try to add unit 621 from 20 th HD.  Usage up to 0.770989704\n",
      "try to add unit 621 from 40 th HD.  Usage up to 0.8088216880000001\n",
      "try to add unit 621 from 60 th HD.  Usage up to 0.8354634080000001\n",
      "try to add unit 621 from 80 th HD.  Usage up to 0.8713056239999999\n",
      "try to add unit 621 from 100 th HD.  Usage up to 0.8940138559999998\n",
      "all done trying to reduce usage of unit 621 final usage = 0.9026 2864 sec elapsed 85 2 successful, failed patches, couldn't start= 20\n",
      "current avg and SD of usage are 0.99947 0.11179\n",
      "starting to increase usage for unit 1043 with usage 0.75428 . Total UU units tried = 25\n",
      "try to add unit 1043 from 0 th HD.  Usage up to 0.7542800319999998\n",
      "try to add unit 1043 from 20 th HD.  Usage up to 0.7919320639999997\n",
      "try to add unit 1043 from 40 th HD.  Usage up to 0.8343130879999997\n",
      "try to add unit 1043 from 60 th HD.  Usage up to 0.8668530479999997\n",
      "try to add unit 1043 from 80 th HD.  Usage up to 0.8969627279999997\n",
      "try to add unit 1043 from 100 th HD.  Usage up to 0.9338644239999996\n",
      "all done trying to reduce usage of unit 1043 final usage = 0.95058 3081 sec elapsed 97 9 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99951 0.10995\n",
      "starting to increase usage for unit 641 with usage 0.75604 . Total UU units tried = 26\n",
      "try to add unit 641 from 0 th HD.  Usage up to 0.7560405279999998\n",
      "try to add unit 641 from 20 th HD.  Usage up to 0.7672818319999999\n",
      "try to add unit 641 from 40 th HD.  Usage up to 0.7777097839999999\n",
      "try to add unit 641 from 60 th HD.  Usage up to 0.7835475759999999\n",
      "try to add unit 641 from 80 th HD.  Usage up to 0.7915161039999999\n",
      "all done trying to reduce usage of unit 641 final usage = 0.7922 3116 sec elapsed 20 4 successful, failed patches, couldn't start= 58\n",
      "current avg and SD of usage are 0.99951 0.10963\n",
      "starting to increase usage for unit 617 with usage 0.75856 . Total UU units tried = 27\n",
      "try to add unit 617 from 0 th HD.  Usage up to 0.7585623039999999\n",
      "try to add unit 617 from 20 th HD.  Usage up to 0.7836557200000001\n",
      "all done trying to reduce usage of unit 617 final usage = 0.79667 3157 sec elapsed 20 3 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 0.99951 0.10923\n",
      "starting to increase usage for unit 2072 with usage 0.75919 . Total UU units tried = 28\n",
      "try to add unit 2072 from 0 th HD.  Usage up to 0.7591900240000005\n",
      "try to add unit 2072 from 20 th HD.  Usage up to 0.8242074640000008\n",
      "try to add unit 2072 from 40 th HD.  Usage up to 0.8899837920000006\n",
      "try to add unit 2072 from 60 th HD.  Usage up to 0.9269436320000003\n",
      "all done trying to reduce usage of unit 2072 final usage = 0.95067 3303 sec elapsed 58 4 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99952 0.1084\n",
      "starting to increase usage for unit 2083 with usage 0.7436 . Total UU units tried = 29\n",
      "try to add unit 2083 from 0 th HD.  Usage up to 0.7436006880000002\n",
      "try to add unit 2083 from 20 th HD.  Usage up to 0.7716228720000002\n",
      "try to add unit 2083 from 40 th HD.  Usage up to 0.8105011520000005\n",
      "try to add unit 2083 from 60 th HD.  Usage up to 0.8364529120000004\n",
      "try to add unit 2083 from 80 th HD.  Usage up to 0.8881575760000003\n",
      "try to add unit 2083 from 100 th HD.  Usage up to 0.9047176880000002\n",
      "try to add unit 2083 from 120 th HD.  Usage up to 0.9426454800000001\n",
      "all done trying to reduce usage of unit 2083 final usage = 0.95201 3495 sec elapsed 65 10 successful, failed patches, couldn't start= 50\n",
      "current avg and SD of usage are 0.99951 0.10749\n",
      "starting to increase usage for unit 2032 with usage 0.74861 . Total UU units tried = 30\n",
      "try to add unit 2032 from 0 th HD.  Usage up to 0.7486113360000002\n",
      "try to add unit 2032 from 20 th HD.  Usage up to 0.7933658960000004\n",
      "try to add unit 2032 from 40 th HD.  Usage up to 0.8298981840000003\n",
      "try to add unit 2032 from 60 th HD.  Usage up to 0.8631610080000005\n",
      "try to add unit 2032 from 80 th HD.  Usage up to 0.9028752800000005\n",
      "all done trying to reduce usage of unit 2032 final usage = 0.9519 3736 sec elapsed 74 6 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 0.99951 0.10683\n",
      "starting to increase usage for unit 624 with usage 0.76257 . Total UU units tried = 31\n",
      "try to add unit 624 from 0 th HD.  Usage up to 0.7625721999999998\n",
      "try to add unit 624 from 20 th HD.  Usage up to 0.796335096\n",
      "try to add unit 624 from 40 th HD.  Usage up to 0.825875176\n",
      "all done trying to reduce usage of unit 624 final usage = 0.83215 3799 sec elapsed 38 4 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 0.99951 0.10623\n",
      "starting to increase usage for unit 595 with usage 0.76516 . Total UU units tried = 32\n",
      "try to add unit 595 from 0 th HD.  Usage up to 0.765155136\n",
      "try to add unit 595 from 20 th HD.  Usage up to 0.8035926480000001\n",
      "try to add unit 595 from 40 th HD.  Usage up to 0.8303458400000001\n",
      "try to add unit 595 from 60 th HD.  Usage up to 0.8690279119999998\n",
      "all done trying to reduce usage of unit 595 final usage = 0.89666 3877 sec elapsed 73 1 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99952 0.10516\n",
      "starting to increase usage for unit 1005 with usage 0.76654 . Total UU units tried = 33\n",
      "try to add unit 1005 from 0 th HD.  Usage up to 0.7665415200000004\n",
      "try to add unit 1005 from 20 th HD.  Usage up to 0.8117741040000004\n",
      "try to add unit 1005 from 40 th HD.  Usage up to 0.8453912880000006\n",
      "try to add unit 1005 from 60 th HD.  Usage up to 0.8671267360000006\n",
      "try to add unit 1005 from 80 th HD.  Usage up to 0.8753351760000005\n",
      "try to add unit 1005 from 100 th HD.  Usage up to 0.8918752080000005\n",
      "try to add unit 1005 from 120 th HD.  Usage up to 0.9087061280000004\n",
      "all done trying to reduce usage of unit 1005 final usage = 0.95346 4095 sec elapsed 84 14 successful, failed patches, couldn't start= 41\n",
      "current avg and SD of usage are 0.99952 0.10372\n",
      "starting to increase usage for unit 619 with usage 0.76808 . Total UU units tried = 34\n",
      "try to add unit 619 from 0 th HD.  Usage up to 0.7680812239999998\n",
      "try to add unit 619 from 20 th HD.  Usage up to 0.7968821599999998\n",
      "try to add unit 619 from 40 th HD.  Usage up to 0.8228386319999998\n",
      "try to add unit 619 from 60 th HD.  Usage up to 0.8594852719999996\n",
      "all done trying to reduce usage of unit 619 final usage = 0.88599 4207 sec elapsed 66 7 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99952 0.10291\n",
      "starting to increase usage for unit 2059 with usage 0.76913 . Total UU units tried = 35\n",
      "try to add unit 2059 from 0 th HD.  Usage up to 0.7691315360000004\n",
      "try to add unit 2059 from 20 th HD.  Usage up to 0.8370477120000003\n",
      "try to add unit 2059 from 40 th HD.  Usage up to 0.8817394320000005\n",
      "try to add unit 2059 from 60 th HD.  Usage up to 0.9315569440000004\n",
      "all done trying to reduce usage of unit 2059 final usage = 0.9504 4394 sec elapsed 57 9 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99952 0.10233\n",
      "starting to increase usage for unit 2063 with usage 0.76802 . Total UU units tried = 36\n",
      "try to add unit 2063 from 0 th HD.  Usage up to 0.7680235439999997\n",
      "try to add unit 2063 from 20 th HD.  Usage up to 0.8244267679999999\n",
      "try to add unit 2063 from 40 th HD.  Usage up to 0.8705045599999999\n",
      "try to add unit 2063 from 60 th HD.  Usage up to 0.926531456\n",
      "all done trying to reduce usage of unit 2063 final usage = 0.95174 4594 sec elapsed 60 11 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99953 0.10184\n",
      "starting to increase usage for unit 937 with usage 0.77265 . Total UU units tried = 37\n",
      "try to add unit 937 from 0 th HD.  Usage up to 0.7726514720000002\n",
      "try to add unit 937 from 20 th HD.  Usage up to 0.7846312800000002\n",
      "try to add unit 937 from 40 th HD.  Usage up to 0.7999646560000002\n",
      "try to add unit 937 from 60 th HD.  Usage up to 0.8222960240000002\n",
      "try to add unit 937 from 80 th HD.  Usage up to 0.8485030320000003\n",
      "try to add unit 937 from 100 th HD.  Usage up to 0.8708872480000003\n",
      "try to add unit 937 from 120 th HD.  Usage up to 0.8827714480000003\n",
      "try to add unit 937 from 140 th HD.  Usage up to 0.9060273040000002\n",
      "try to add unit 937 from 160 th HD.  Usage up to 0.940719712\n",
      "all done trying to reduce usage of unit 937 final usage = 0.95045 4852 sec elapsed 75 32 successful, failed patches, couldn't start= 57\n",
      "current avg and SD of usage are 0.99953 0.10066\n",
      "starting to increase usage for unit 2070 with usage 0.77284 . Total UU units tried = 38\n",
      "try to add unit 2070 from 0 th HD.  Usage up to 0.7728374080000001\n",
      "try to add unit 2070 from 20 th HD.  Usage up to 0.8241139520000004\n",
      "try to add unit 2070 from 40 th HD.  Usage up to 0.8674679840000005\n",
      "try to add unit 2070 from 60 th HD.  Usage up to 0.9081257040000006\n",
      "try to add unit 2070 from 80 th HD.  Usage up to 0.9287902480000005\n",
      "all done trying to reduce usage of unit 2070 final usage = 0.95024 5116 sec elapsed 63 19 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 0.99953 0.10015\n",
      "starting to increase usage for unit 1089 with usage 0.7725 . Total UU units tried = 39\n",
      "try to add unit 1089 from 0 th HD.  Usage up to 0.7724989999999998\n",
      "try to add unit 1089 from 20 th HD.  Usage up to 0.8360432240000001\n",
      "try to add unit 1089 from 40 th HD.  Usage up to 0.9075216560000001\n",
      "all done trying to reduce usage of unit 1089 final usage = 0.95149 5224 sec elapsed 50 3 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 0.99955 0.09898\n",
      "starting to increase usage for unit 2085 with usage 0.77355 . Total UU units tried = 40\n",
      "try to add unit 2085 from 0 th HD.  Usage up to 0.7735521120000001\n",
      "try to add unit 2085 from 20 th HD.  Usage up to 0.844077272\n",
      "try to add unit 2085 from 40 th HD.  Usage up to 0.8977674880000003\n",
      "try to add unit 2085 from 60 th HD.  Usage up to 0.9339036800000003\n",
      "all done trying to reduce usage of unit 2085 final usage = 0.95018 5414 sec elapsed 51 13 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 0.99955 0.09853\n",
      "starting to increase usage for unit 605 with usage 0.77492 . Total UU units tried = 41\n",
      "try to add unit 605 from 0 th HD.  Usage up to 0.774919096\n",
      "try to add unit 605 from 20 th HD.  Usage up to 0.8051665280000002\n",
      "try to add unit 605 from 40 th HD.  Usage up to 0.8244598720000001\n",
      "try to add unit 605 from 60 th HD.  Usage up to 0.8469090240000001\n",
      "try to add unit 605 from 80 th HD.  Usage up to 0.8669993840000001\n",
      "try to add unit 605 from 100 th HD.  Usage up to 0.889832512\n",
      "try to add unit 605 from 120 th HD.  Usage up to 0.9120273359999999\n",
      "try to add unit 605 from 140 th HD.  Usage up to 0.9384407119999998\n",
      "all done trying to reduce usage of unit 605 final usage = 0.95151 5566 sec elapsed 99 0 successful, failed patches, couldn't start= 49\n",
      "current avg and SD of usage are 0.99955 0.0972\n",
      "starting to increase usage for unit 526 with usage 0.77777 . Total UU units tried = 42\n",
      "try to add unit 526 from 0 th HD.  Usage up to 0.7777659039999998\n",
      "try to add unit 526 from 20 th HD.  Usage up to 0.8155165279999999\n",
      "try to add unit 526 from 40 th HD.  Usage up to 0.8379314719999997\n",
      "try to add unit 526 from 60 th HD.  Usage up to 0.8695241919999995\n",
      "try to add unit 526 from 80 th HD.  Usage up to 0.8982162799999994\n",
      "all done trying to reduce usage of unit 526 final usage = 0.90753 5716 sec elapsed 76 6 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 0.99956 0.09647\n",
      "starting to increase usage for unit 9 with usage 0.7773 . Total UU units tried = 43\n",
      "try to add unit 9 from 0 th HD.  Usage up to 0.777304424\n",
      "try to add unit 9 from 20 th HD.  Usage up to 0.808555712\n",
      "try to add unit 9 from 40 th HD.  Usage up to 0.8276821759999999\n",
      "try to add unit 9 from 60 th HD.  Usage up to 0.8446896880000001\n",
      "try to add unit 9 from 80 th HD.  Usage up to 0.856810832\n",
      "try to add unit 9 from 100 th HD.  Usage up to 0.870447432\n",
      "try to add unit 9 from 120 th HD.  Usage up to 0.8845695919999998\n",
      "try to add unit 9 from 140 th HD.  Usage up to 0.9000174079999999\n",
      "try to add unit 9 from 160 th HD.  Usage up to 0.9090445199999998\n",
      "try to add unit 9 from 180 th HD.  Usage up to 0.9160282239999998\n",
      "try to add unit 9 from 200 th HD.  Usage up to 0.9254599359999999\n",
      "all done trying to reduce usage of unit 9 final usage = 0.92546 5941 sec elapsed 84 11 successful, failed patches, couldn't start= 108\n",
      "current avg and SD of usage are 0.99956 0.09552\n",
      "starting to increase usage for unit 1068 with usage 0.78249 . Total UU units tried = 44\n",
      "try to add unit 1068 from 0 th HD.  Usage up to 0.7824893680000002\n",
      "try to add unit 1068 from 20 th HD.  Usage up to 0.8415096400000002\n",
      "try to add unit 1068 from 40 th HD.  Usage up to 0.8957943040000002\n",
      "try to add unit 1068 from 60 th HD.  Usage up to 0.9476901920000005\n",
      "all done trying to reduce usage of unit 1068 final usage = 0.9579 6061 sec elapsed 57 4 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99957 0.09442\n",
      "starting to increase usage for unit 2077 with usage 0.78196 . Total UU units tried = 45\n",
      "try to add unit 2077 from 0 th HD.  Usage up to 0.7819639920000002\n",
      "try to add unit 2077 from 20 th HD.  Usage up to 0.8245487280000003\n",
      "try to add unit 2077 from 40 th HD.  Usage up to 0.8802633040000005\n",
      "try to add unit 2077 from 60 th HD.  Usage up to 0.8995157120000006\n",
      "try to add unit 2077 from 80 th HD.  Usage up to 0.9478822480000003\n",
      "all done trying to reduce usage of unit 2077 final usage = 0.95087 6274 sec elapsed 49 14 successful, failed patches, couldn't start= 21\n",
      "current avg and SD of usage are 0.99957 0.09406\n",
      "starting to increase usage for unit 2080 with usage 0.78147 . Total UU units tried = 46\n",
      "try to add unit 2080 from 0 th HD.  Usage up to 0.7814695200000003\n",
      "try to add unit 2080 from 20 th HD.  Usage up to 0.8164626960000001\n",
      "try to add unit 2080 from 40 th HD.  Usage up to 0.8795081200000002\n",
      "try to add unit 2080 from 60 th HD.  Usage up to 0.9262482240000002\n",
      "all done trying to reduce usage of unit 2080 final usage = 0.95014 6496 sec elapsed 52 15 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99957 0.09369\n",
      "starting to increase usage for unit 1490 with usage 0.78653 . Total UU units tried = 47\n",
      "try to add unit 1490 from 0 th HD.  Usage up to 0.78653392\n",
      "try to add unit 1490 from 20 th HD.  Usage up to 0.8185673920000001\n",
      "try to add unit 1490 from 40 th HD.  Usage up to 0.8458251039999999\n",
      "try to add unit 1490 from 60 th HD.  Usage up to 0.8671742719999999\n",
      "try to add unit 1490 from 80 th HD.  Usage up to 0.8835311679999998\n",
      "all done trying to reduce usage of unit 1490 final usage = 0.89103 6652 sec elapsed 48 20 successful, failed patches, couldn't start= 23\n",
      "current avg and SD of usage are 0.99958 0.09323\n",
      "starting to increase usage for unit 1501 with usage 0.78782 . Total UU units tried = 48\n",
      "try to add unit 1501 from 0 th HD.  Usage up to 0.7878168319999999\n",
      "try to add unit 1501 from 20 th HD.  Usage up to 0.794761408\n",
      "try to add unit 1501 from 40 th HD.  Usage up to 0.8067208079999998\n",
      "try to add unit 1501 from 60 th HD.  Usage up to 0.8094781279999997\n",
      "try to add unit 1501 from 80 th HD.  Usage up to 0.8228061919999997\n",
      "all done trying to reduce usage of unit 1501 final usage = 0.83393 6801 sec elapsed 26 67 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99958 0.09299\n",
      "starting to increase usage for unit 519 with usage 0.78829 . Total UU units tried = 49\n",
      "try to add unit 519 from 0 th HD.  Usage up to 0.7882936879999997\n",
      "try to add unit 519 from 20 th HD.  Usage up to 0.7902529119999997\n",
      "try to add unit 519 from 40 th HD.  Usage up to 0.7955292479999997\n",
      "try to add unit 519 from 60 th HD.  Usage up to 0.7955292479999997\n",
      "try to add unit 519 from 80 th HD.  Usage up to 0.8012877599999997\n",
      "all done trying to reduce usage of unit 519 final usage = 0.81527 6929 sec elapsed 13 81 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99958 0.09287\n",
      "starting to increase usage for unit 28 with usage 0.78947 . Total UU units tried = 50\n",
      "try to add unit 28 from 0 th HD.  Usage up to 0.7894720399999996\n",
      "try to add unit 28 from 20 th HD.  Usage up to 0.8159340399999997\n",
      "try to add unit 28 from 40 th HD.  Usage up to 0.8446864159999999\n",
      "try to add unit 28 from 60 th HD.  Usage up to 0.8615511199999999\n",
      "try to add unit 28 from 80 th HD.  Usage up to 0.872617648\n",
      "try to add unit 28 from 100 th HD.  Usage up to 0.8894737039999998\n",
      "try to add unit 28 from 120 th HD.  Usage up to 0.9092280079999997\n",
      "try to add unit 28 from 140 th HD.  Usage up to 0.9225989599999997\n",
      "all done trying to reduce usage of unit 28 final usage = 0.95263 7229 sec elapsed 63 68 successful, failed patches, couldn't start= 28\n",
      "current avg and SD of usage are 0.99959 0.09253\n",
      "starting to increase usage for unit 640 with usage 0.78976 . Total UU units tried = 51\n",
      "try to add unit 640 from 0 th HD.  Usage up to 0.7897642639999997\n",
      "try to add unit 640 from 20 th HD.  Usage up to 0.7975498959999997\n",
      "try to add unit 640 from 40 th HD.  Usage up to 0.7992125999999997\n",
      "try to add unit 640 from 60 th HD.  Usage up to 0.8023481919999997\n",
      "try to add unit 640 from 80 th HD.  Usage up to 0.8071991439999996\n",
      "try to add unit 640 from 100 th HD.  Usage up to 0.8150097839999996\n",
      "all done trying to reduce usage of unit 640 final usage = 0.82738 7339 sec elapsed 18 66 successful, failed patches, couldn't start= 23\n",
      "current avg and SD of usage are 0.99959 0.09226\n",
      "starting to increase usage for unit 2082 with usage 0.79184 . Total UU units tried = 52\n",
      "try to add unit 2082 from 0 th HD.  Usage up to 0.7918445760000001\n",
      "try to add unit 2082 from 20 th HD.  Usage up to 0.809516392\n",
      "try to add unit 2082 from 40 th HD.  Usage up to 0.8127074080000001\n",
      "try to add unit 2082 from 60 th HD.  Usage up to 0.8231935520000001\n",
      "try to add unit 2082 from 80 th HD.  Usage up to 0.84816188\n",
      "try to add unit 2082 from 100 th HD.  Usage up to 0.84816188\n",
      "try to add unit 2082 from 120 th HD.  Usage up to 0.84816188\n",
      "try to add unit 2082 from 140 th HD.  Usage up to 0.84816188\n",
      "all done trying to reduce usage of unit 2082 final usage = 0.85285 7533 sec elapsed 12 95 successful, failed patches, couldn't start= 35\n",
      "current avg and SD of usage are 0.9996 0.09218\n",
      "starting to increase usage for unit 1053 with usage 0.79036 . Total UU units tried = 53\n",
      "try to add unit 1053 from 0 th HD.  Usage up to 0.7903639360000001\n",
      "try to add unit 1053 from 20 th HD.  Usage up to 0.8004468720000001\n",
      "try to add unit 1053 from 40 th HD.  Usage up to 0.8224486560000002\n",
      "try to add unit 1053 from 60 th HD.  Usage up to 0.8369738000000002\n",
      "try to add unit 1053 from 80 th HD.  Usage up to 0.8570963280000001\n",
      "try to add unit 1053 from 100 th HD.  Usage up to 0.8813327120000004\n",
      "all done trying to reduce usage of unit 1053 final usage = 0.88292 7706 sec elapsed 46 53 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 0.9996 0.09146\n",
      "starting to increase usage for unit 2068 with usage 0.79248 . Total UU units tried = 54\n",
      "try to add unit 2068 from 0 th HD.  Usage up to 0.7924814879999998\n",
      "try to add unit 2068 from 20 th HD.  Usage up to 0.7938282799999998\n",
      "try to add unit 2068 from 40 th HD.  Usage up to 0.8003266959999998\n",
      "try to add unit 2068 from 60 th HD.  Usage up to 0.8053466879999999\n",
      "try to add unit 2068 from 80 th HD.  Usage up to 0.8179309439999998\n",
      "all done trying to reduce usage of unit 2068 final usage = 0.81793 7873 sec elapsed 10 75 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 0.99961 0.09139\n",
      "starting to increase usage for unit 1495 with usage 0.79632 . Total UU units tried = 55\n",
      "try to add unit 1495 from 0 th HD.  Usage up to 0.79631804\n",
      "try to add unit 1495 from 20 th HD.  Usage up to 0.799094768\n",
      "try to add unit 1495 from 40 th HD.  Usage up to 0.799094768\n",
      "all done trying to reduce usage of unit 1495 final usage = 0.8025 7923 sec elapsed 4 35 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 0.99961 0.09137\n",
      "starting to increase usage for unit 1210 with usage 0.79814 . Total UU units tried = 56\n",
      "try to add unit 1210 from 0 th HD.  Usage up to 0.7981417120000003\n",
      "try to add unit 1210 from 20 th HD.  Usage up to 0.8377263040000003\n",
      "try to add unit 1210 from 40 th HD.  Usage up to 0.8784183040000003\n",
      "try to add unit 1210 from 60 th HD.  Usage up to 0.9184590880000002\n",
      "try to add unit 1210 from 80 th HD.  Usage up to 0.9435160400000001\n",
      "all done trying to reduce usage of unit 1210 final usage = 0.95258 8040 sec elapsed 55 25 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99963 0.09004\n"
     ]
    }
   ],
   "source": [
    "#FIRST PATCHING BLOCK - boosting underuse.  Works OK.\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used\")\n",
    "maxSD = 0.05  #0.07\n",
    "stopMinUse = 1. - maxSD\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"this block is a WIP - let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the avg no of units per district\n",
    "attemptedSmallUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to increase usage for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Total UU units tried =\",len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    idx0 = np.argsort(uuuDists)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs): #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "861f29d3-b727-49af-90a8-aa9a963e0741",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 0.99903 0.99963 and their SDs are 0.15874 0.09004\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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uDqrxer1KT0+3ak7m9/vV0NAQ9AIAAOevLp+JeeSRR+Tz+fTtb39bERERamlp0S9/+UvdcccdkqTa2lpJktvtDnqf2+3W3r17rZro6Gj17du3Tc2J95+sqKhITzzxRFd/OwAAIEx1+UzMK6+8ouXLl2vFihWqqKjQ0qVL9cwzz2jp0qVBdQ6HI+hrY0ybfSc7U82sWbPk8/ms1/79+8/tGwEAAGGty2di/v3f/10zZ87U7bffLknKyMjQ3r17VVRUpLvuuksej0dSYLblggsusN5XV1dnzc54PB41NTWpvr4+aDamrq5O2dnZp/zvOp1OOZ08JhsAOuuYidY17y+ytoFw1+Uh5ujRo+rVK3iCJyIiwrrFeuDAgfJ4PCotLdUVV1whSWpqatL69ev19NNPS5IyMzMVFRWl0tJS5efnS5JqampUVVWlOXPmdHXLAABJRr10oDn4VP+AmatD1E3n7XlqbKhbwFeky0PMjTfeqF/+8pfq37+/Lr30Um3btk1z587V3XffLSlwGqmgoECFhYVKS0tTWlqaCgsLFRsbq/Hjx0uSXC6XJk2apOnTpyspKUmJiYmaMWOGMjIyrLuVAABAz9blIeY3v/mNfvazn2nKlCmqq6uT1+vV5MmT9fOf/9yqefjhh9XY2KgpU6aovr5eWVlZWrt2reLj462aefPmKTIyUvn5+WpsbNSIESO0ZMkSRUREdHXLAABJUY5mzfAskyQ9UztRzSw7gDDnMMaYUDfRHRoaGuRyueTz+ZSQkBDqdgAg7E/NxDiO6f2MWyVJg7a/qkbTO8QddQ6nk+ytI7+/WTsJAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYUpc/JwYAYE/HTLRGffhbaxsId4QYAICkwLIDu/wXhroNoN04nQQAAGyJmRgAgKTAsgP3p/xRkvTbunyWHUDYI8QAACRJkWpRgftlSdJzdbeoWYQYhDdOJwEAAFsixAAAAFsixAAAAFsixAAAAFviwl4AtjRg5upQtwAgxJiJAQAAtsRMDABAkuQ3UcrbNdfaBsIdIQYAIElqVYTebfxWqNsA2o3TSQAAwJaYiQEASAosO/Dj5FWSpMX/zGPZAYQ9QgwAQFJg2YH/e8FiSdKyf45l2QGEPU4nAQAAWyLEAAAAWyLEAAAAWyLEAAAAWyLEAAAAWyLEAAAAW+IWawCApMBSA7d/VGhtA+GOEAMAkBRYdmDTl5eFug2g3TidBAAAbImZGACAJClSx3VH0hpJ0sufj9FxfkUgzPETCgCQJEU5jusX3/idJOnVL0bquOFXBMIbp5MAAIAtEWIAAIAtEWIAAIAtEWIAAIAtEWIAAIAtEWIAAIAtcf8cAECS1GSi9OPqx61tINwRYgAAkqQWReitw1eFug2g3TidBAAAbImZGACApMCyAzf3/X+SpJX1w1l2AGGPn1AAgKTAsgPPpM6XJK0+dA3LDiDscToJAADYEiEGAADYEiEGAADYUreEmE8++UT/9m//pqSkJMXGxuo73/mOysvLrePGGM2ePVter1cxMTEaPny4duzYEfQZfr9fU6dOVXJysuLi4pSXl6cDBw50R7sAAMCGujzE1NfX63vf+56ioqL0X//1X3rvvff061//Wn369LFq5syZo7lz52rBggXaunWrPB6PRo0apcOHD1s1BQUFKikpUXFxsTZs2KAjR44oNzdXLS0tXd0yAACwoS6/9Pzpp59WamqqFi9ebO0bMGCAtW2M0fz58/Xoo49q3LhxkqSlS5fK7XZrxYoVmjx5snw+nxYtWqRly5Zp5MiRkqTly5crNTVV69at0+jRo7u6bQAAYDNdPhOzatUqDRkyRD/84Q+VkpKiK664Qi+88IJ1vLq6WrW1tcrJybH2OZ1ODRs2TGVlZZKk8vJyNTc3B9V4vV6lp6dbNQCArtVkojRl70xN2TuTZQdgC10eYj7++GM9++yzSktL09/+9jfdd999evDBB/XSSy9JkmprayVJbrc76H1ut9s6Vltbq+joaPXt2/e0NSfz+/1qaGgIegEA2q9FEXrdd41e912jFkWEuh3grLr8dFJra6uGDBmiwsJCSdIVV1yhHTt26Nlnn9Wdd95p1TkcjqD3GWPa7DvZmWqKior0xBNPnGP3AADALrp8JuaCCy7Q4MGDg/YNGjRI+/btkyR5PB5JajOjUldXZ83OeDweNTU1qb6+/rQ1J5s1a5Z8Pp/12r9/f5d8PwDQU0SoRT9wbdAPXBsUIW6iQPjr8hDzve99Tx9++GHQvp07d+rCCy+UJA0cOFAej0elpaXW8aamJq1fv17Z2dmSpMzMTEVFRQXV1NTUqKqqyqo5mdPpVEJCQtALANB+0Y5mLbzwKS288ClFO5pD3Q5wVl1+Oumhhx5Sdna2CgsLlZ+fry1btuj555/X888/LylwGqmgoECFhYVKS0tTWlqaCgsLFRsbq/Hjx0uSXC6XJk2apOnTpyspKUmJiYmaMWOGMjIyrLuVAABAz9blIeaqq65SSUmJZs2apSeffFIDBw7U/PnzNWHCBKvm4YcfVmNjo6ZMmaL6+nplZWVp7dq1io+Pt2rmzZunyMhI5efnq7GxUSNGjNCSJUsUEcHFZgAAQHIYY0yom+gODQ0Ncrlc8vl8nFoCzkMDZq4OdQvnnRjHMb2fcaskadD2V9Voeoe4o87Z89TYULeAc9CR39+snQQAAGyJEAMAAGyJEAMAAGypyy/sBQDYU7OJ1Iz9BdY2EO74KQUASJKOK1Kv1vMYC9gHp5MAAIAtMRMDAJAUWHbg+/EVkqS3D1/JIpAIe4QYAICkwLIDiwcGFtINPCeGEIPwxukkAABgS4QYAABgS4QYAABgS4QYAABgS4QYAABgS4QYAABgS9xiDQCQFFhq4Gef3GdtA+GOn1IAgKTAsgPLPs8NdRtAu3E6CQAA2BIzMQAASVIvtei7cTskSVu+vFStLDuAMEeIAQBIkpyOZhVf/H8lsewA7IHTSQAAwJYIMQAAwJYIMQAAwJYIMQAAwJYIMQAAwJYIMQAAwJa4xRoAIEk6rggV1vzY2gbCHSEGACBJajZRev6zW0LdBtBunE4CAAC2xEwMAEBSYNmB9JiPJElVjRez7ADCHiEGACApsOzAqrRpklh2APbA6SQAAGBLhBgAAGBLhBgAAGBLhBgAAGBLhBgAAGBLhBgAAGBL3GINAJAUWGpg/qd3WNtAuCPEAAAkBZYdmP/phFC3AbQbp5MAAIAtMRMDAJAkOdSqbzr3S5J2+1Nl+DsXYY4QAwCQJPV2NKn0kvslnVh2oHeIOwLOjJgNAABsiRADAABsiRADAABsiRADAABsiRADAABsiRADAABsiVusAQCSAksNPPfZOGsbCHfdPhNTVFQkh8OhgoICa58xRrNnz5bX61VMTIyGDx+uHTt2BL3P7/dr6tSpSk5OVlxcnPLy8nTgwIHubhcAeqxmE6WimrtVVHO3mk1UqNsBzqpbQ8zWrVv1/PPP67LLLgvaP2fOHM2dO1cLFizQ1q1b5fF4NGrUKB0+fNiqKSgoUElJiYqLi7VhwwYdOXJEubm5amlp6c6WAQCATXRbiDly5IgmTJigF154QX379rX2G2M0f/58Pfrooxo3bpzS09O1dOlSHT16VCtWrJAk+Xw+LVq0SL/+9a81cuRIXXHFFVq+fLm2b9+udevWdVfLANCjOdSqflGfql/Up3KoNdTtAGfVbSHm/vvv19ixYzVy5Mig/dXV1aqtrVVOTo61z+l0atiwYSorK5MklZeXq7m5OajG6/UqPT3dqjmZ3+9XQ0ND0AsA0H69HU3aMGiSNgyapN6OplC3A5xVt1zYW1xcrIqKCm3durXNsdraWkmS2+0O2u92u7V3716rJjo6OmgG50TNifefrKioSE888URXtA8AAGygy2di9u/fr5/+9Kdavny5evc+/eJhDocj6GtjTJt9JztTzaxZs+Tz+azX/v37O948AACwjS4PMeXl5aqrq1NmZqYiIyMVGRmp9evX6z//8z8VGRlpzcCcPKNSV1dnHfN4PGpqalJ9ff1pa07mdDqVkJAQ9AIAAOevLg8xI0aM0Pbt21VZWWm9hgwZogkTJqiyslIXXXSRPB6PSktLrfc0NTVp/fr1ys7OliRlZmYqKioqqKampkZVVVVWDQAA6Nm6/JqY+Ph4paenB+2Li4tTUlKStb+goECFhYVKS0tTWlqaCgsLFRsbq/Hjx0uSXC6XJk2apOnTpyspKUmJiYmaMWOGMjIy2lwoDAAAeqaQPLH34YcfVmNjo6ZMmaL6+nplZWVp7dq1io+Pt2rmzZunyMhI5efnq7GxUSNGjNCSJUsUEcFTJAEAgOQwxphQN9EdGhoa5HK55PP5uD4GOA8NmLk61C2cd6IdzXrsgt9Lkv6j5h412fSpvXueGhvqFnAOOvL7m7WTAACSpCYTpZ8f/D+hbgNoN1axBgAAtsRMDADgX4wSIwJPO/+iJUHSmZ/dBYQaIQYAIEmKcfhVcekESdKg7a+q0Zz+gaVAOOB0EgAAsCVCDAAAsCVCDAAAsCVCDAAAsCVCDAAAsCVCDAAAsCVusQYASJJaFKFXvxhhbQPhjhADAJAUWHZgxoGHQt0G0G6cTgIAALbETAwA4F+MYhx+SVKjcYplBxDumIkBAEgKLDvwfsatej/jVivMAOGMEAMAAGyJEAMAAGyJEAMAAGyJEAMAAGyJEAMAAGyJEAMAAGyJ58QAACRJreql1Ye+Z20D4Y4QAwCQJPlNtO7fNyvUbQDtRtQGAAC2xEwMAOC8MmDm6lC30Cl7nhob6hZsh5kYAIAkKcZxTHsuy9Wey3IV4zgW6naAsyLEAAAAWyLEAAAAWyLEAAAAWyLEAAAAWyLEAAAAWyLEAAAAW+I5MQAASYGlBt5sGGJtA+GOEAMAkBRYduDuPbND3QbQbkRtAABgS4QYAABgS4QYAICkwLID76XfovfSb2HZAdgC18QAACyxvfyhbgFoN2ZiAACALRFiAACALRFiAACALRFiAACALRFiAACALXF3EgBAktQqhzYdSbe2gXBHiAEASJL8xqnbP34q1G0A7cbpJAAAYEuEGAAAYEuEGACApMCyA+WDx6t88HiWHYAtdHmIKSoq0lVXXaX4+HilpKTo5ptv1ocffhhUY4zR7Nmz5fV6FRMTo+HDh2vHjh1BNX6/X1OnTlVycrLi4uKUl5enAwcOdHW7AID/JSmyQUmRDaFuA2iXLg8x69ev1/33369NmzaptLRUx48fV05Ojr788kurZs6cOZo7d64WLFigrVu3yuPxaNSoUTp8+LBVU1BQoJKSEhUXF2vDhg06cuSIcnNz1dLS0tUtAwAAG+ryu5PWrFkT9PXixYuVkpKi8vJyff/735cxRvPnz9ejjz6qcePGSZKWLl0qt9utFStWaPLkyfL5fFq0aJGWLVumkSNHSpKWL1+u1NRUrVu3TqNHj+7qtgEAgM10+zUxPp9PkpSYmChJqq6uVm1trXJycqwap9OpYcOGqaysTJJUXl6u5ubmoBqv16v09HSr5mR+v18NDQ1BLwAAcP7q1hBjjNG0adN0zTXXKD098ACl2tpaSZLb7Q6qdbvd1rHa2lpFR0erb9++p605WVFRkVwul/VKTU3t6m8HAACEkW4NMQ888IDeffddvfzyy22OORzBT4M0xrTZd7Iz1cyaNUs+n8967d+/v/ONAwCAsNdtT+ydOnWqVq1apbffflv9+vWz9ns8HkmB2ZYLLrjA2l9XV2fNzng8HjU1Nam+vj5oNqaurk7Z2dmn/O85nU45nc7u+FYAoEdolUP/OJpmbQPhrstnYowxeuCBB/Taa6/pzTff1MCBA4OODxw4UB6PR6Wlpda+pqYmrV+/3goomZmZioqKCqqpqalRVVXVaUMMAODc+I1TN+2ep5t2z5Pf8Echwl+Xz8Tcf//9WrFihf7yl78oPj7euobF5XIpJiZGDodDBQUFKiwsVFpamtLS0lRYWKjY2FiNHz/eqp00aZKmT5+upKQkJSYmasaMGcrIyLDuVgIAAD1bl4eYZ599VpI0fPjwoP2LFy/Wj370I0nSww8/rMbGRk2ZMkX19fXKysrS2rVrFR8fb9XPmzdPkZGRys/PV2Njo0aMGKElS5YoIiKiq1sGAAA25DDGmFA30R0aGhrkcrnk8/mUkJAQ6nYAdLEBM1eHuoXzTm/HMa27ZIokaeSHC3XM9A5xRz3LnqfGhrqFsNCR39/ddmEvAMBeHJL6RddZ20C4YwFIAABgS4QYAABgS4QYAABgS4QYAABgS4QYAABgS9ydBACQJBlJO4/1t7aBcEeIAQBIko6Z3srZuTDUbQDtxukkAABgS4QYAABgS4QYAICkwLIDa781RWu/NUW9HcdC3Q5wVlwTAwCQFFhq4Fu991nbQLhjJgYAANgSIQYAANgSIQYAANgSIQYAANgSIQYAANgSdycBACQFlho40JRibQPhjhADAJAUWHbgmg9eDHUbQLtxOgkAANgSIQYAANgSIQYAIElyOvz6yzcf0l+++ZCcDn+o2wHOimtiAACSpF4yujx2l7UNhDtmYgAAgC0RYgAAgC0RYgAAgC0RYgAAgC0RYgAAgC1xdxIAwPL58YRQtwC0GyEGACBJajS9lfneilC3AbQbp5MAAIAtEWIAAIAtEWIAAJICyw4UXzRTxRfNZNkB2ALXxAAAJAWWGrj6a1XWNhDumIkBAAC2RIgBAAC2RIgBAAC2RIgBAAC2RIgBAAC2xN1JAADL0VZnqFsA2o0QAwCQFFh2YHDVn0PdBtBunE4CAAC2xExMJw2YuTrULXTYnqfGhroFAAC6DDMxAABJktPRpBcHzNaLA2bL6WgKdTvAWTET04MwewTgTHqpVdcnvGNtA+GOmRgAAGBLzMQAABAGmC3vuLAPMQsXLtSvfvUr1dTU6NJLL9X8+fN17bXXhrotfEX4Rw0AOJ2wPp30yiuvqKCgQI8++qi2bduma6+9VjfccIP27dsX6tYAAECIhXWImTt3riZNmqR77rlHgwYN0vz585Wamqpnn3021K0BAIAQC9vTSU1NTSovL9fMmTOD9ufk5KisrKxNvd/vl9/vt772+XySpIaGhm7pr9V/tFs+F/bXXT9zCMa/wa7X4jimhn8Na4v/qFoNdyjhzLrj/3cnPtMYc9basA0x//znP9XS0iK32x203+12q7a2tk19UVGRnnjiiTb7U1NTu61H4FRc80PdAdB5LmvrzhB2Abvozv/fHT58WC6X64w1YRtiTnA4HEFfG2Pa7JOkWbNmadq0adbXra2t+uKLL5SUlHTKenReQ0ODUlNTtX//fiUkJIS6nfMKY9s9GNfuw9h2n546tsYYHT58WF6v96y1YRtikpOTFRER0WbWpa6urs3sjCQ5nU45ncGrr/bp06c7W+zxEhISetQ/rK8SY9s9GNfuw9h2n544tmebgTkhbC/sjY6OVmZmpkpLS4P2l5aWKjs7O0RdAQCAcBG2MzGSNG3aNE2cOFFDhgzR0KFD9fzzz2vfvn267777Qt0aAAAIsbAOMbfddps+//xzPfnkk6qpqVF6erpef/11XXjhhaFurUdzOp16/PHH25y+w7ljbLsH49p9GNvuw9iencO05x4mAACAMBO218QAAACcCSEGAADYEiEGAADYEiEGAADYEiHmPDNgwAA5HI42r/vvv1+S9Nprr2n06NFKTk6Ww+FQZWXlKT9n48aNuv766xUXF6c+ffpo+PDhamxstI7X19dr4sSJcrlccrlcmjhxog4dOhT0Gfv27dONN96ouLg4JScn68EHH1RTU1NQzfbt2zVs2DDFxMToG9/4hp588sl2rZcRCl0xtrW1tZo4caI8Ho/i4uJ05ZVX6tVXXw2qYWyDx7a5uVmPPPKIMjIyFBcXJ6/XqzvvvFMHDx4M+gy/36+pU6cqOTlZcXFxysvL04EDB4JqGNuOj+0XX3yhqVOn6pJLLlFsbKz69++vBx980Fqf7oSeNrZd8TN7gjFGN9xwgxwOh1auXBl0rKeNa4cZnFfq6upMTU2N9SotLTWSzFtvvWWMMeall14yTzzxhHnhhReMJLNt27Y2n1FWVmYSEhJMUVGRqaqqMjt37jR/+tOfzLFjx6yaMWPGmPT0dFNWVmbKyspMenq6yc3NtY4fP37cpKenm+uuu85UVFSY0tJS4/V6zQMPPGDV+Hw+43a7ze233262b99u/vznP5v4+HjzzDPPdNv4nIuuGNuRI0eaq666ymzevNl89NFH5he/+IXp1auXqaiosGoY2+CxPXTokBk5cqR55ZVXzAcffGA2btxosrKyTGZmZtBn3HfffeYb3/iGKS0tNRUVFea6664zl19+uTl+/LhVw9h2fGy3b99uxo0bZ1atWmV2795t3njjDZOWlmZuueWWoP9OTxvbrviZPWHu3LnmhhtuMJJMSUlJ0LGeNq4dRYg5z/30pz81F198sWltbQ3aX11dfdpftFlZWeaxxx477We+9957RpLZtGmTtW/jxo1Gkvnggw+MMca8/vrrplevXuaTTz6xal5++WXjdDqNz+czxhizcOFC43K5gsJRUVGR8Xq9bfoNR50Z27i4OPPSSy8F7UtMTDS///3vjTGM7QmnG9sTtmzZYiSZvXv3GmOMOXTokImKijLFxcVWzSeffGJ69epl1qxZY4xhbE/o6Nieyh//+EcTHR1tmpubjTGMrTGdH9fKykrTr18/U1NT0ybEMK5nx+mk81hTU5OWL1+uu+++u92LYNbV1Wnz5s1KSUlRdna23G63hg0bpg0bNlg1GzdulMvlUlZWlrXv6quvlsvlUllZmVWTnp4etIDX6NGj5ff7VV5ebtUMGzYs6EFOo0eP1sGDB7Vnz55z+da7XWfGVpKuueYavfLKK/riiy/U2tqq4uJi+f1+DR8+XBJjK7VvbH0+nxwOh7U+Wnl5uZqbm5WTk2PVeL1epaenB40bY9vxsT1dTUJCgiIjA89L7elj29lxPXr0qO644w4tWLBAHo+nzXt6+ri2ByHmPLZy5UodOnRIP/rRj9r9no8//liSNHv2bN17771as2aNrrzySo0YMUK7du2SFLiuIyUlpc17U1JSrAU7a2tr2yzU2bdvX0VHR5+x5sTXJy/8GW46M7aS9Morr+j48eNKSkqS0+nU5MmTVVJSoosvvlgSYyudfWyPHTummTNnavz48daieLW1tYqOjlbfvn2Dat1ud9CYMLYdH9uTff755/rFL36hyZMnW/t6+th2dlwfeughZWdn66abbjrl+3r6uLZHWC87gHOzaNEi3XDDDe1azvyE1tZWSdLkyZP14x//WJJ0xRVX6I033tCLL76ooqIiSTrlXxvGmKD9nakx/7rQrCOzG6HQmbGVpMcee0z19fVat26dkpOTtXLlSv3whz/U3//+d2VkZEhibM80ts3Nzbr99tvV2tqqhQsXnvWzumLc2lPTU8a2oaFBY8eO1eDBg/X4448HHevJY9uZcV21apXefPNNbdu27Yyf3ZPHtT2YiTlP7d27V+vWrdM999zTofddcMEFkqTBgwcH7R80aJD27dsnSfJ4PPr000/bvPezzz6z0r3H42mT8Ovr69Xc3HzGmrq6Oklq81dDOOns2H700UdasGCBXnzxRY0YMUKXX365Hn/8cQ0ZMkS//e1vJTG2Zxrb5uZm5efnq7q6WqWlpUF/0Xo8HjU1Nam+vj7oPXV1dUFjwth2fGxPOHz4sMaMGaOvfe1rKikpUVRUlHWsJ49tZ8f1zTff1EcffaQ+ffooMjLSOjV3yy23WKeXe/K4thch5jy1ePFipaSkaOzYsR1634ABA+T1evXhhx8G7d+5c6e18ObQoUPl8/m0ZcsW6/jmzZvl8/mUnZ1t1VRVVammpsaqWbt2rZxOpzIzM62at99+O+hWwLVr18rr9WrAgAEd6vur1NmxPXr0qCSpV6/gf3YRERHWDBhje+qxPfHLYNeuXVq3bp2SkpKCjmdmZioqKkqlpaXWvpqaGlVVVQWNG2Pb8bGVAjMwOTk5io6O1qpVq9S7d++g4z15bDs7rjNnztS7776ryspK6yVJ8+bN0+LFiyX17HFtt6/+WmJ0t5aWFtO/f3/zyCOPtDn2+eefm23btpnVq1cbSaa4uNhs27bN1NTUWDXz5s0zCQkJ5k9/+pPZtWuXeeyxx0zv3r3N7t27rZoxY8aYyy67zGzcuNFs3LjRZGRknPK2vxEjRpiKigqzbt06069fv6Db/g4dOmTcbre54447zPbt281rr71mEhISwvq2v3MZ26amJvPNb37TXHvttWbz5s1m9+7d5plnnjEOh8OsXr3a+hzGNnhsm5ubTV5enunXr5+prKwMuq3V7/dbdffdd5/p16+fWbdunamoqDDXX3/9KW+xZmz/R3vGtqGhwWRlZZmMjAyze/fuoJqePrbn+jN7Mp3mFuueNq4dQYg5D/3tb38zksyHH37Y5tjixYuNpDavxx9/PKiuqKjI9OvXz8TGxpqhQ4eav//970HHP//8czNhwgQTHx9v4uPjzYQJE0x9fX1Qzd69e83YsWNNTEyMSUxMNA888EDQLX7GGPPuu++aa6+91jidTuPxeMzs2bPD+pa/cx3bnTt3mnHjxpmUlBQTGxtrLrvssja3XDO2wWN74pb1U71OPKPHGGMaGxvNAw88YBITE01MTIzJzc01+/btC/osxrbjY/vWW2+dtqa6utr6rJ44tuf6M3uyU4WYnjiuHeEw5nx4ZB8AAOhpuCYGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADYEiEGAADY0v8H8AeyMQgmy44AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 3108\n",
      "working on HD 300 out of 3108\n",
      "working on HD 600 out of 3108\n",
      "working on HD 900 out of 3108\n",
      "working on HD 1200 out of 3108\n",
      "working on HD 1500 out of 3108\n",
      "working on HD 1800 out of 3108\n",
      "working on HD 2100 out of 3108\n",
      "working on HD 2400 out of 3108\n",
      "working on HD 2700 out of 3108\n",
      "working on HD 3000 out of 3108\n",
      "all done checking HD and complement contiguity for all 3108 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb30c52b-cedb-43cf-a39a-589bb4b71c5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#2/14/24 plan -- re-read in the unpatched HDvtdList\n",
    "# update OUU code to match UUU code in terms of legit swaps, nCouldntStart, etc\n",
    "# check that unitUse up and down are properly calculated\n",
    "# start a running list of OUU's with more fails than patches -- are they all in E-NE?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d42dc91-6d8c-4ef5-8fa1-297f746a9aa5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "77c07848-50c2-4fe9-8841-768b02bf4ac4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 36085\n",
      "current avg and SD of unit usage are 0.99963 0.07486 . Now trying to reduce up to 26 units' overusage\n",
      "starting to reduce usage for unit 373 with usage 1.21053 . Total units tried = 1\n",
      "try to drop unit 373 from 20 th HD.  usage down to 1.181679975999999\n",
      "try to drop unit 373 from 40 th HD.  usage down to 1.1530439999999988\n",
      "try to drop unit 373 from 60 th HD.  usage down to 1.135390199999999\n",
      "try to drop unit 373 from 80 th HD.  usage down to 1.129713439999999\n",
      "try to drop unit 373 from 100 th HD.  usage down to 1.115511143999999\n",
      "all done trying to increase usage of unit 373 final usage = 1.11098 8 sec elapsed 39 64 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99962 0.07326\n",
      "starting to reduce usage for unit 156 with usage 1.19182 . Total units tried = 2\n",
      "try to drop unit 156 from 41 th HD.  usage down to 1.1133316480000002\n",
      "all done trying to increase usage of unit 156 final usage = 1.02684 29 sec elapsed 56 0 successful, failed patches, couldn't start= 24\n",
      "current avg and SD of usage are 0.99961 0.0713\n",
      "starting to reduce usage for unit 377 with usage 1.16273 . Total units tried = 3\n",
      "try to drop unit 377 from 16 th HD.  usage down to 1.127353775999999\n",
      "try to drop unit 377 from 32 th HD.  usage down to 1.1180315279999988\n",
      "try to drop unit 377 from 48 th HD.  usage down to 1.0993523839999988\n",
      "try to drop unit 377 from 64 th HD.  usage down to 1.0807979519999988\n",
      "try to drop unit 377 from 80 th HD.  usage down to 1.0664418559999989\n",
      "all done trying to increase usage of unit 377 final usage = 1.065 39 sec elapsed 33 49 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 0.99961 0.06993\n",
      "starting to reduce usage for unit 391 with usage 1.14834 . Total units tried = 4\n",
      "try to drop unit 391 from 18 th HD.  usage down to 1.1455965440000004\n",
      "try to drop unit 391 from 36 th HD.  usage down to 1.1455965440000004\n",
      "try to drop unit 391 from 54 th HD.  usage down to 1.1349773840000006\n",
      "try to drop unit 391 from 72 th HD.  usage down to 1.1299172080000006\n",
      "try to drop unit 391 from 90 th HD.  usage down to 1.1253724720000007\n",
      "all done trying to increase usage of unit 391 final usage = 1.12042 45 sec elapsed 7 86 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.9996 0.06956\n",
      "starting to reduce usage for unit 2323 with usage 1.13962 . Total units tried = 5\n",
      "try to drop unit 2323 from 19 th HD.  usage down to 1.1157250079999987\n",
      "try to drop unit 2323 from 38 th HD.  usage down to 1.0920549679999991\n",
      "try to drop unit 2323 from 57 th HD.  usage down to 1.072683319999999\n",
      "try to drop unit 2323 from 76 th HD.  usage down to 1.0606231519999991\n",
      "try to drop unit 2323 from 95 th HD.  usage down to 1.050768831999999\n",
      "all done trying to increase usage of unit 2323 final usage = 1.04624 56 sec elapsed 39 55 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.9996 0.06831\n",
      "starting to reduce usage for unit 2301 with usage 1.13685 . Total units tried = 6\n",
      "try to drop unit 2301 from 19 th HD.  usage down to 1.1368546080000004\n",
      "try to drop unit 2301 from 38 th HD.  usage down to 1.1368546080000004\n",
      "try to drop unit 2301 from 57 th HD.  usage down to 1.1306928960000004\n",
      "try to drop unit 2301 from 76 th HD.  usage down to 1.1227964240000006\n",
      "try to drop unit 2301 from 95 th HD.  usage down to 1.0978599600000003\n",
      "all done trying to increase usage of unit 2301 final usage = 1.09435 65 sec elapsed 16 81 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.9996 0.06777\n",
      "starting to reduce usage for unit 1286 with usage 1.14051 . Total units tried = 7\n",
      "try to drop unit 1286 from 17 th HD.  usage down to 1.128636423999999\n",
      "try to drop unit 1286 from 34 th HD.  usage down to 1.1117640959999988\n",
      "try to drop unit 1286 from 51 th HD.  usage down to 1.0826432559999988\n",
      "try to drop unit 1286 from 68 th HD.  usage down to 1.0547707279999987\n",
      "all done trying to increase usage of unit 1286 final usage = 1.02964 84 sec elapsed 48 22 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 0.9996 0.06639\n",
      "starting to reduce usage for unit 493 with usage 1.13253 . Total units tried = 8\n",
      "try to drop unit 493 from 20 th HD.  usage down to 1.131139304000002\n",
      "try to drop unit 493 from 40 th HD.  usage down to 1.131139304000002\n",
      "try to drop unit 493 from 60 th HD.  usage down to 1.131139304000002\n",
      "try to drop unit 493 from 80 th HD.  usage down to 1.131139304000002\n",
      "try to drop unit 493 from 100 th HD.  usage down to 1.131139304000002\n",
      "all done trying to increase usage of unit 493 final usage = 1.13114 92 sec elapsed 1 101 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 0.9996 0.06637\n",
      "starting to reduce usage for unit 250 with usage 1.12933 . Total units tried = 9\n",
      "try to drop unit 250 from 20 th HD.  usage down to 1.1160363600000003\n",
      "try to drop unit 250 from 40 th HD.  usage down to 1.1160363600000003\n",
      "try to drop unit 250 from 60 th HD.  usage down to 1.1160363600000003\n",
      "try to drop unit 250 from 80 th HD.  usage down to 1.1160363600000003\n",
      "try to drop unit 250 from 100 th HD.  usage down to 1.1115331920000002\n",
      "all done trying to increase usage of unit 250 final usage = 1.11153 99 sec elapsed 9 89 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.9996 0.06614\n",
      "starting to reduce usage for unit 182 with usage 1.12945 . Total units tried = 10\n",
      "try to drop unit 182 from 16 th HD.  usage down to 1.1294488880000007\n",
      "try to drop unit 182 from 32 th HD.  usage down to 1.1294488880000007\n",
      "try to drop unit 182 from 48 th HD.  usage down to 1.1294488880000007\n",
      "try to drop unit 182 from 64 th HD.  usage down to 1.1294488880000007\n",
      "try to drop unit 182 from 80 th HD.  usage down to 1.1294488880000007\n",
      "all done trying to increase usage of unit 182 final usage = 1.12945 105 sec elapsed 0 84 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 0.9996 0.06614\n",
      "starting to reduce usage for unit 2186 with usage 1.12051 . Total units tried = 11\n",
      "try to drop unit 2186 from 20 th HD.  usage down to 1.1205130480000012\n",
      "try to drop unit 2186 from 40 th HD.  usage down to 1.1205130480000012\n",
      "try to drop unit 2186 from 60 th HD.  usage down to 1.1205130480000012\n",
      "try to drop unit 2186 from 80 th HD.  usage down to 1.118771360000001\n",
      "try to drop unit 2186 from 100 th HD.  usage down to 1.089985728000001\n",
      "all done trying to increase usage of unit 2186 final usage = 1.08672 115 sec elapsed 13 85 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 0.9996 0.06572\n",
      "starting to reduce usage for unit 192 with usage 1.12015 . Total units tried = 12\n",
      "try to drop unit 192 from 19 th HD.  usage down to 1.1201518080000012\n",
      "try to drop unit 192 from 38 th HD.  usage down to 1.1201518080000012\n",
      "try to drop unit 192 from 57 th HD.  usage down to 1.1201518080000012\n",
      "try to drop unit 192 from 76 th HD.  usage down to 1.1201518080000012\n",
      "try to drop unit 192 from 95 th HD.  usage down to 1.1147383120000012\n",
      "all done trying to increase usage of unit 192 final usage = 1.11474 122 sec elapsed 2 88 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 0.9996 0.06565\n",
      "starting to reduce usage for unit 190 with usage 1.11932 . Total units tried = 13\n",
      "try to drop unit 190 from 16 th HD.  usage down to 1.119320120000002\n",
      "try to drop unit 190 from 32 th HD.  usage down to 1.119320120000002\n",
      "try to drop unit 190 from 48 th HD.  usage down to 1.119320120000002\n",
      "try to drop unit 190 from 64 th HD.  usage down to 1.119320120000002\n",
      "try to drop unit 190 from 80 th HD.  usage down to 1.119320120000002\n",
      "all done trying to increase usage of unit 190 final usage = 1.11932 130 sec elapsed 0 80 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.9996 0.06565\n",
      "starting to reduce usage for unit 1102 with usage 1.11551 . Total units tried = 14\n",
      "try to drop unit 1102 from 16 th HD.  usage down to 1.1155053839999995\n",
      "try to drop unit 1102 from 32 th HD.  usage down to 1.1021859119999995\n",
      "try to drop unit 1102 from 48 th HD.  usage down to 1.0639533199999998\n",
      "try to drop unit 1102 from 64 th HD.  usage down to 1.0390999999999997\n",
      "all done trying to increase usage of unit 1102 final usage = 1.02905 141 sec elapsed 32 30 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99959 0.06466\n",
      "starting to reduce usage for unit 2205 with usage 1.11108 . Total units tried = 15\n",
      "try to drop unit 2205 from 17 th HD.  usage down to 1.1110780239999987\n",
      "try to drop unit 2205 from 34 th HD.  usage down to 1.1090398239999986\n",
      "try to drop unit 2205 from 51 th HD.  usage down to 1.0985897039999986\n",
      "try to drop unit 2205 from 68 th HD.  usage down to 1.0952559759999985\n",
      "try to drop unit 2205 from 85 th HD.  usage down to 1.0756249279999985\n",
      "all done trying to increase usage of unit 2205 final usage = 1.06983 148 sec elapsed 11 77 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99959 0.06419\n",
      "starting to reduce usage for unit 826 with usage 1.11014 . Total units tried = 16\n",
      "try to drop unit 826 from 18 th HD.  usage down to 1.074352696\n",
      "try to drop unit 826 from 36 th HD.  usage down to 1.0302964719999996\n",
      "all done trying to increase usage of unit 826 final usage = 1.02805 157 sec elapsed 31 5 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 0.99959 0.06269\n",
      "starting to reduce usage for unit 2193 with usage 1.10919 . Total units tried = 17\n",
      "try to drop unit 2193 from 19 th HD.  usage down to 1.109192592000001\n",
      "try to drop unit 2193 from 38 th HD.  usage down to 1.109192592000001\n",
      "try to drop unit 2193 from 57 th HD.  usage down to 1.109192592000001\n",
      "try to drop unit 2193 from 76 th HD.  usage down to 1.109192592000001\n",
      "try to drop unit 2193 from 95 th HD.  usage down to 1.109192592000001\n",
      "all done trying to increase usage of unit 2193 final usage = 1.10919 167 sec elapsed 0 94 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99959 0.06269\n",
      "starting to reduce usage for unit 2309 with usage 1.10847 . Total units tried = 18\n",
      "try to drop unit 2309 from 19 th HD.  usage down to 1.1084665840000003\n",
      "try to drop unit 2309 from 38 th HD.  usage down to 1.1084665840000003\n",
      "try to drop unit 2309 from 57 th HD.  usage down to 1.1084665840000003\n",
      "try to drop unit 2309 from 76 th HD.  usage down to 1.1053018960000003\n",
      "try to drop unit 2309 from 95 th HD.  usage down to 1.1053018960000003\n",
      "all done trying to increase usage of unit 2309 final usage = 1.1053 173 sec elapsed 1 91 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99959 0.06265\n",
      "starting to reduce usage for unit 394 with usage 1.10736 . Total units tried = 19\n",
      "try to drop unit 394 from 19 th HD.  usage down to 1.1073611680000006\n",
      "try to drop unit 394 from 38 th HD.  usage down to 1.1046149280000006\n",
      "try to drop unit 394 from 57 th HD.  usage down to 1.1046149280000006\n",
      "try to drop unit 394 from 76 th HD.  usage down to 1.1046149280000006\n",
      "try to drop unit 394 from 95 th HD.  usage down to 1.1046149280000006\n",
      "all done trying to increase usage of unit 394 final usage = 1.10461 182 sec elapsed 1 85 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 0.99959 0.06262\n",
      "starting to reduce usage for unit 191 with usage 1.10836 . Total units tried = 20\n",
      "try to drop unit 191 from 19 th HD.  usage down to 1.1083618320000006\n",
      "try to drop unit 191 from 38 th HD.  usage down to 1.1083618320000006\n",
      "try to drop unit 191 from 57 th HD.  usage down to 1.1083618320000006\n",
      "try to drop unit 191 from 76 th HD.  usage down to 1.1083618320000006\n",
      "try to drop unit 191 from 95 th HD.  usage down to 1.0981846800000008\n",
      "all done trying to increase usage of unit 191 final usage = 1.09818 190 sec elapsed 4 85 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 0.99959 0.06248\n",
      "starting to reduce usage for unit 1150 with usage 1.10652 . Total units tried = 21\n",
      "try to drop unit 1150 from 21 th HD.  usage down to 1.1065183280000002\n",
      "try to drop unit 1150 from 42 th HD.  usage down to 1.093425888\n",
      "try to drop unit 1150 from 63 th HD.  usage down to 1.053728744\n",
      "all done trying to increase usage of unit 1150 final usage = 1.02782 201 sec elapsed 30 44 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 0.99959 0.06159\n",
      "starting to reduce usage for unit 278 with usage 1.10534 . Total units tried = 22\n",
      "try to drop unit 278 from 16 th HD.  usage down to 1.1033856719999997\n",
      "try to drop unit 278 from 32 th HD.  usage down to 1.1012172239999998\n",
      "try to drop unit 278 from 48 th HD.  usage down to 1.0997083199999997\n",
      "try to drop unit 278 from 64 th HD.  usage down to 1.0972627519999998\n",
      "try to drop unit 278 from 80 th HD.  usage down to 1.0958730079999999\n",
      "all done trying to increase usage of unit 278 final usage = 1.0863 209 sec elapsed 8 74 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 0.99958 0.06134\n",
      "starting to reduce usage for unit 309 with usage 1.10233 . Total units tried = 23\n",
      "try to drop unit 309 from 17 th HD.  usage down to 1.0997516319999983\n",
      "try to drop unit 309 from 34 th HD.  usage down to 1.0888203839999984\n",
      "try to drop unit 309 from 51 th HD.  usage down to 1.0748023759999983\n",
      "try to drop unit 309 from 68 th HD.  usage down to 1.0645157519999984\n",
      "try to drop unit 309 from 85 th HD.  usage down to 1.0527701119999981\n",
      "all done trying to increase usage of unit 309 final usage = 1.05065 217 sec elapsed 19 64 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99959 0.0608\n",
      "starting to reduce usage for unit 2311 with usage 1.10125 . Total units tried = 24\n",
      "try to drop unit 2311 from 20 th HD.  usage down to 1.1012463840000013\n",
      "try to drop unit 2311 from 40 th HD.  usage down to 1.1012463840000013\n",
      "try to drop unit 2311 from 60 th HD.  usage down to 1.0963968240000015\n",
      "try to drop unit 2311 from 80 th HD.  usage down to 1.0963968240000015\n",
      "try to drop unit 2311 from 100 th HD.  usage down to 1.0816361360000013\n",
      "all done trying to increase usage of unit 2311 final usage = 1.07429 231 sec elapsed 12 83 successful, failed patches, couldn't start= 9\n",
      "current avg and SD of usage are 0.99959 0.06043\n",
      "starting to reduce usage for unit 174 with usage 1.0969 . Total units tried = 25\n",
      "try to drop unit 174 from 11 th HD.  usage down to 1.0944597359999986\n",
      "try to drop unit 174 from 22 th HD.  usage down to 1.0846345199999985\n",
      "try to drop unit 174 from 33 th HD.  usage down to 1.0846345199999985\n",
      "try to drop unit 174 from 44 th HD.  usage down to 1.0761075999999985\n",
      "try to drop unit 174 from 55 th HD.  usage down to 1.0761075999999985\n",
      "all done trying to increase usage of unit 174 final usage = 1.07108 239 sec elapsed 8 51 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99959 0.06019\n",
      "starting to reduce usage for unit 1230 with usage 1.09649 . Total units tried = 26\n",
      "try to drop unit 1230 from 16 th HD.  usage down to 1.0964911199999987\n",
      "try to drop unit 1230 from 32 th HD.  usage down to 1.0869983759999988\n",
      "try to drop unit 1230 from 48 th HD.  usage down to 1.0808962319999986\n",
      "try to drop unit 1230 from 64 th HD.  usage down to 1.0694193839999986\n",
      "try to drop unit 1230 from 80 th HD.  usage down to 1.0507014559999985\n",
      "all done trying to increase usage of unit 1230 final usage = 1.04584 249 sec elapsed 23 39 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 0.99959 0.05965\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS  #for CO, run this first as we have a right-tailed distro.  Ran again after Denver triage\n",
    "maxSD = 0.06\n",
    "stopMaxUse = 1.+0.5*maxSD\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the districts a unit is drawn into\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #each round, find the (5) most overused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nBigFound, bigUsers = 0,0,list()\n",
    "    while nBigFound < nBigUsers:\n",
    "        consideredBigU = idx[-idxNo-1]\n",
    "        if consideredBigU not in attemptedBigUs:\n",
    "            bigUsers.append(consideredBigU)\n",
    "            nBigFound +=1\n",
    "        idxNo +=1\n",
    "    OUUclusters = [ [b] + unitNbrs[b] for b in bigUsers ]\n",
    "    bigOverUse = [np.sum([(unitUse[j] - 1.) for j in OUUclusters[i] ]) for i in range(nBigUsers) ]\n",
    "    bigI = bigOverUse.index(np.max(bigOverUse))\n",
    "    OUU = bigUsers[ bigI ]  #pick the unit that centers cluster with most overuse\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    OUUc = OUUclusters[bigI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUU2nbrSet = set( unitNbrs[OUU])\n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.union(set(unitNbrs[u])) \n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.difference({u})\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUU2nbrSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0,0,0,0, np.argsort(ouuDists)\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.5*len(ouuHDs): #arbitrarily only examine 50% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True\n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            tryPop = np.sum([unitPop[u] for u in trySet])\n",
    "            \n",
    "            legitSwap = False\n",
    "            if abs(gap) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "            \n",
    "    print(\"all done trying to increase usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n",
    "            \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "ecd50c96-51ce-4d83-b0df-e8c645c35815",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    }
   ],
   "source": [
    "print(\"after above patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        for i,uu in enumerate(surrounders):\n",
    "            if u == uu:\n",
    "                unitVTDlist[u].append(surroundedVTDs[i])\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        vtdList[t] += unitVTDlist[u]\n",
    "    #add more stuff here to convert to vtd lists\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"contigPatchEvenMore.csv\"   #patchDown, PatchUp, PatchBoth, contigPatchUpBetter\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a779738d-4417-45b8-9c5f-07953e84acd6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "above OUU contig cluster has pop 302708\n"
     ]
    }
   ],
   "source": [
    "#2/16/24 - run an alternate patching that seeks to drop specific overused blue urban Denver precincts\n",
    "# ideally, we replace these with underused CCB 2\n",
    "OUVcluster = [290, 292, 299, 301, 302, 306, 307, 308, 309, 310, 311, 317, 318, 319, 327, 328, 329, 340, 344, 346, 355, 357, 385, 387, 388, 389, 390, 391, 392, 393, \n",
    "              398, 399, 400, 407, 408, 415, 416, 419, 420, 422, 424, 425, 427, 428, 429, 430, 436, 440, 446, 453, 459, 460, 461, 467, 472, 473, 478, 480, 484, 486, \n",
    "              487, 488, 494, 495, 503, 504, 509, 510, 513, 514, 515, 519, 521, 522, 527, 528, 531, 572, 583, 584, 588, 589, 593, 601, 602, 606, 607, 608, 609, 610, \n",
    "              615, 617, 618, 625, 626, 630, 632, 633, 637, 642, 643, 644, 645, 646, 1031, 1351, 1358, 1375, 1419, 1477, 1918, 1945, 1971, 1972, 1976, 2026,\n",
    "              2096, 2097, 2098, 2099, 2105, 2111, 2143, 2165, 2166, 2196, 2447, 2456, 2462, 2471, 2477, 2548, 2557, 2564, 2568, 2569, 2589, 2595]\n",
    "OUUcluster = [allUnits.index(v) for v in OUVcluster] \n",
    "OUUcontig = getContigFromStarter(OUUcluster[11],OUUcluster,unitNbrs)\n",
    "for u in OUUcontig:\n",
    "    plotPoly(unitGeom[u])\n",
    "    plotCenter(\".\",unitGeom[u])\n",
    "plotPoly(countyGeom[16])\n",
    "plt.show()\n",
    "OUUcPop = np.sum([unitPop[u] for u in OUUcontig])\n",
    "print(\"above OUU contig cluster has pop\",OUUcPop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f3d35498-085e-4db7-baa2-4764eb3cb722",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will ID all HDs that currently have some of the overused cluster on a boundary AND neighbor the UUU 2822 with pop 105949.0 or one of its neighbors\n",
      "working on HD 0\n",
      "working on HD 200\n",
      "working on HD 400\n",
      "working on HD 600\n",
      "working on HD 800\n",
      "working on HD 1000\n",
      "working on HD 1200\n",
      "working on HD 1400\n",
      "working on HD 1600\n",
      "working on HD 1800\n",
      "working on HD 2000\n",
      "working on HD 2200\n",
      "working on HD 2400\n",
      "working on HD 2600\n",
      "working on HD 2800\n",
      "working on HD 3000\n",
      "I found  5 that could potentially jettison Denver pop for SW corner\n",
      "Here are the swap-out Pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "UUU = 2822 #this is CCB 2\n",
    "print(\"we will ID all HDs that currently have some of the overused cluster on a boundary AND neighbor the UUU\",UUU,\n",
    "      \"with pop\",unitPop[UUU],\"or one of its neighbors\")\n",
    "UUc = [UUU] + unitNbrs[UUU]\n",
    "swapCandidates, swapPops = list(), list()\n",
    "for t in range(nHDs):\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "    if len(HDadjoinSet.intersection(set(UUc)) ) > 0:  #could easily add the underused corner\n",
    "        HDouus = set(OUUcontig).intersection(set(HDunitList[t]) )\n",
    "        ouuAdjoinSet = HDadjoinSet.intersection(set (getAdjoiners(HDouus,unitNbrs)) )\n",
    "        if len(ouuAdjoinSet) > 0:  #the OUU cluster is on the boundary; we can jettison some of it cleanly\n",
    "            swapCandidates.append(t)\n",
    "            swapPops.append(np.sum([unitPop[u] for u in HDouus] ) )\n",
    "print(\"I found \",len(swapCandidates),\"that could potentially jettison Denver pop for SW corner\")\n",
    "print(\"Here are the swap-out Pop distro\")\n",
    "plt.hist(swapPops)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b9008834-4bf5-464c-88f7-4d65ad792ddb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KjVGRFhYhKpOSnovRS49VTqEKUS9p/actXfgdJPmKEBVrFxLI5XwLF7PztA5FCOFC7nLA7vJTQvWTDMQiREU+WHuE11YcRFEg2FRLneGFELVL4yYWSVgcYJutWTIWIa6WmZvPx+uPMWf1YfQ6hWk3d5JRoYUQNUISFgfJNliI0lbtP8uc1Ye5sUsIb43tho9BOtwKIWqG9GERQlRZZGN/ADo1D5JkRYh6T9tzQpKwOEhaWIQorWhG5i5hQRpHIoSoKe5ymlcSFkeoIL1uhSitSYCtg60MFCeEqGmSsAghqizfYgUgLSdf40iEEDVN1fgqIUlYhBBVptfZWh63HrugcSRCiPpOEhYhRJV1CDFxU0wovx+RhEWIek9aWIQQdZnJ1yCd0oWoz9zk71vGYRFCOCU338Ke0+nodQo+Bj2Jp9Lxk063QogaJgmLEMIpb648yMfrj9mf6xT45sFYDSMqyWpVycorwGpVKbCqWIruLSoWVcVLp+DtpcOg1+HtpcNY+FgIUTGtJz+UhEUI4ZQtxy4C0K9NYyb1a0nnsCDCGvhWu9xvtiQxdUkiXjoFRblqOgylxB3eXjp8DHq8C5MOg17BoLclHscvZDt91dLOF4bTyN+72nUQoj5yl1O+krAIIZzy+u1d+Xj9Ub7ffYZ9yRm8f3ePaicsFqvK1CWJAPRr24ThHZvZXys6qiu6pFJVVfIsVnLzreQVWMm3WDEX3ucVWBkU1YR2IYF46XR46RT0hTcvnYJOp1BgUTEXWLh//nYAhkcH09DPUK34hfAIGl/XLAmLA9wkuRTCLbQPCeSNO7ryzPXteeiLHcxacYAv/9IXc4EFP6MXAUbnNyvrDqUC8Pg1bXn82rY1Psy/xWrb8N7QOYS59/Ss0c8Sou5zj72gJCyOco/vSwi30SzQh/v6t2RyfAJdX1ppX35XnwhmjIlxqqz4rScB+NvQthi9ar4Db05eAQAN/OQ0kBB1hfQ0E0JU2YhOITwypA1jeoTx8i2d6RrRgAWFyYczDqdmAZCbZ3V1iKXEb02iy4u2BGvB1iSSLuTU+GcKUR9Ip1shRJ3lY9Dz7PUd7M//t+s0ABeyzDQunGcIbP1OyptATVVVzmeaua9/S4JqoS/JpqNXBrlrEuCNl16aT4WoiHS6FULUO31bNWLHiUv0fGUVX97fhwCjF39bsIvUDDNtmwUQ27oxyemX6dOqEWN7ReBv9CItJ59Mc0GtjeVy/Hw2t3YP4+1x3Wrl84QQriGnhIQQLvPM9R24J7YFABM+3coHa//k1KXL/GVAK9qHBPL9H2dYvieFad/vo9O/f+Y/6/5EX9jCseXoxRqP72BKJomn0+nTqlGNf5YQ9Y7G54SkhUUI4VIvj+7MmB7hjPlgI7/sO0v/to35vxtsp41UVeVMei4/7D7DdztOMXP5AWYuPwBA+mXXz/hsLrAw46cDZJkLMOh1LNiaRIeQQG7u2tzlnyWEqFmSsAghXEpRFHq0aMiAtk3YcOQ8k4e2K/FaWANf/jq4DX8Z0Ir5G49z6tJlRsaEEtUswOWxnL50mXkbj9OmqT8GvY7whr7Mvacn/lW49FoIjyctLEKI+uirB/pitarodGX32DPodTwwsHWNxhDgY9vETbmhI8Oig2v0s4Sot9yk0630YRFC1JjykpXaUmCxHRLKlUBC1H2SsAgh6q2ihMXbSzZ1QlSXqvE5IfkrFkLUS6mZuTzy9Q4A/L3l7LcQVVXeGEq1Tf6KhRD1zqlLOdzzyRayzAU8dk0buoQFaR2SEHWfdLoVQojqOXEhm9X7U0lOv8zq/akcPZ+Nr0HPz08OokVjP63DE0K4gCQsQog67dj5bK55Yy2KAhEN/egSHsQ1HZrx10GtaWby0To8IYSLSMIihKiz5m88zr+X7QVgzd+H0LKJv8YRCVF/aT35YbU63c6YMQNFUXjyySfty1RV5cUXX6R58+b4+voyZMgQ9u7dW2lZixYtIjo6GqPRSHR0NEuWLKlOaEKIei7LXGBPVgBJVoSoIW7S57bqCcu2bdv46KOPiImJKbH8tdde46233uK9995j27ZthISEMHz4cDIzM8sta9OmTYwbN44JEyawe/duJkyYwNixY9myZUtVwxNC1GPnMs10/vfP9uf+3nrMBRYNIxJC1LQqJSxZWVmMHz+ejz/+mIYNG9qXq6rK7Nmzee655xgzZgydO3dm/vz55OTk8M0335Rb3uzZsxk+fDhTpkyhQ4cOTJkyhaFDhzJ79uyqhCeEqKd+3ptCy//7kX4zV5dYnp1nYfHO0xpFJYSH0PicUJUSlscee4yRI0cybNiwEsuPHTtGSkoK1113nX2Z0Whk8ODBbNy4sdzyNm3aVOI9ACNGjKjwPUIIz5Obb2tFybeo9lmhi0xZnMjDX+7QIiwh6jn3OCfkdKfb+Ph4du7cybZt20q9lpKSAkBwcMk5O4KDgzlx4kS5ZaakpJT5nqLyymI2mzGbzfbnGRkZDsUvhKi7runQzP74q81JAHQJCyLxdDoAHUNNmsQlhCdQ1To00u3JkyeZPHkyX331FT4+5V8uePWoeKqqVjpSnrPvmTFjBkFBQfZbRESEAzUQQtRlJh8Dd/Wx/a2/eUdX3ryjK6mZuYCtH8tj17TRMjwh6iV36XTrVAvLjh07SE1NpWfPnvZlFouF3377jffee4+DBw8CthaT0NBQ+zqpqamlWlCKCwkJKdWaUtl7pkyZwtNPP21/npGRUaNJi5t8X0J4vBljYrirTwse+Wonp9Muc037prx7V1t6t2zoNkOICyFcz6kWlqFDh5KYmEhCQoL91qtXL8aPH09CQgKtW7cmJCSEX375xf6evLw81q1bR79+/cotNy4ursR7AFauXFnhe4xGIyaTqcRNCOEZfkxM5nTaZR4d0ob/TOhJn1aNJFkRop5zqoUlMDCQzp07l1jm7+9P48aN7cuffPJJXn31VaKiooiKiuLVV1/Fz8+Pu+++2/6eiRMnEhYWxowZMwCYPHkygwYNYtasWYwePZqlS5eyatUqNmzYUN36CSHqoaJZmD9Y+yfbT1ziy/v7YPTSaxyVEPWUmxwLuHyk22eeeYbLly/z6KOPcunSJfr27cvKlSsJDAy0r5OUlIROd6Vxp1+/fsTHx/P888/zwgsv0KZNG7799lv69u3r6vCEEPXA365ty9AOzUhOz2XKkkTun7cdf6Oehn7ePDeyI4E+Bq1DFEK4WLUTlrVr15Z4rigKL774Ii+++KLD7wG4/fbbuf3226sbjvBAyemXOX4+B6NBh9FLh49Bj9FLh9FLT4DRC19vOfKubxr4edOvbRMA/Lz1PPrNToouYBjTI5w+rRppGJ0Q9ZTM1ixE9fztm11sP3GpzNd0CmyaMpRgmQSv3rqhSyj7X7qevWfSuW3uJs0vvXRGwaVLHLt1DAUpKQTdNgb/2FgUvR7/fv3QN2igdXhCuBVJWESddznfws1dm/PYNW0xF1gwF1gx51tZtf8s8zYeJ99i1TpEUcN8DLbTQXWFmp/PpYULOf/+B1guXAAgfdFi0hcttq8TMHgwjR98AL9evbQKU4gStD4UkIRF1AtBvgbahwSWWHY538K8jcelM6aHKLpKSOuNqiNy9+7l7Esvg5cXAYMHEz73A9SCArBYuDh/Prn79pO5ciXGdu0kYRGac5cr8Ko1W7MQ7qC8MwB5BbaWFW8v+Zl7EvfYtFbMmpcHQJsffyDiw/+g6HTovL3R+frS+K9/RefnB4BiNGoZphBuRbbkot7Ks9jmnTFKwiLcTUGB7V5fupE7//QZ0v/3P9DraXz/X2o3LiEqonH/MDklJOqFslos7S0seklYROWOnc8m6WIOn204Rl6BlUHtmvLIENcO9a+qKuZDh7n8xx8AKIbSm2A19zIAkV9+ic7X16WfL0RdJgmLqLfyCqwY9Ao6XV04SSCqqzpXB/15Louhb64rsWzT0Qus2JPM09e1Z3C7ptWKzZKZyfGx48g7dqzEcp2/f6l1rZdtcyPpfOR0kHAvWl+AJwmLqJZL2Xl8veUE+Zbyf8kqYC6wkHG5gMzcfDJyC+8v55OZW0C+xYpep8NLp6DXKXjpFfSK7bFOUeytJ4qioGBrTVEUULC9dvR8Fr1aNiz1ueYCq7SuiAqpqsqCrSd5Z/UhAP45oj0XsvKIbd2Ij9cfZdvxS2z883y1E5aC8+fJO3aMoNE3Yz56zHbZclAQ2b9vtHe6UXQ60OvJO3rU9ryCCWaFqE1u0udWEhZRPWsPpfLGykMEm4woFXR3NBp0mHwMmHy9CDQaCDEZCfQxYPIxYPBSsFpVCqwqlmL3RTew7VhUwKqqqKotCbJl+yqdmpu4tXtYqc/Ms1ilw60o19QliXyzJcn+vEtYEPf0jSTIzzZK7kNf7gAgJqyBw2WqViuXFizAmpNDg9tuw6tRyQHs9E2akLt0GbmJiRWWoxgM6BuWTsKF8GSSsIhqKRriZMOz12Jws9aMvAJJWERpBRYrCSfTSiQrTQKMfP+3Afbn/1n3p/3xyJhQypKfkgIWC4YwW7Jszckh9Y03ufTNN7bPOXeOgMGDURQF8/HjAKhm29VBodOnY2zfHu+IcFBVrNnZHJ8wAa/GTQh//z10vr7oAwPL/FwhPJUkLKJaivoNuEmLYQmSsHgWR0+vL955mmcW/VFiWbCpZH+Ro+ey7I93fLWExssXoeh05CQk4BsdjVfzUDKXrwBA37gxepMJn+hoMn780f6+S198yaUvvixRrneLFgAkP/cc3m3a0ObHH2xlNGhA1K+/OlgDIWqZm2zgJWER1VK0k3CXgYWKy5M+LB6lqENgZb/F2NaNSzx/YEArRnQOKbHsv9tP2R9nL1mM394dGCJbQH4+lvR0FL8rV+/4dOxI9oYN9g61URvWo/j4YE1PR1VV8k+fAVXFcukiBefO02rpUtK+jSdrvcxGL4QzJGER1VO0k9A2ijLZ+rDIKLeeo7C1r5IfY0SjkpcKf7XlBFNu7FhiWWzrRmw+epFPJ/Wic2YwZydOIPSll/Hv26fMMnP37SPv+HG8QkLwatIE89GjnH1lOtkbN5YbR9GpJCHqDLlKSNRlqoM7CS3kFVjJzbdoHYaoJaqDyfOZ9NwSzzuGmtBfdel7WAM/ekWqnEnP5ZcdF5gEqAX55ZbpEx2NT3Q0AJf++19SX38Da2YmAP794mj84IMAXE7cQ0FqKopej0+XLo5XTggNVXRBRW2ShEVUi9bX5VekWaCR1IxcrFZVxmLxAFdOT5a/zuGzmTzy9U4AZo/rxvWdQ/AxlN0Kl5pp5oX/7aHx5XQmATk5ZgIqiSE/NZWUf/3bFofRSOjLLxF088321/3j4hysjRDuR9W4iUVO8Itqcec+LF56HYqiaN2KKWrJleS57N9iXoGV2/+ziSOpWXw0oSe3dA8rN1lp2diPpIs5ABTobJvJn/84XWkM+adsfV/C33+PDrsTSiQrQtRZbrJ5l4RFVIs7t7BczM6jgZ+hVHO/qJ/KOz1pLrBwOu0yBr1CoI8XXcODGNYxuMKy/jY0iuMzR3J85khu6BYOgMmB9mh9gwYAnHrscVSr1ek6CCHKJwmLqDY3bFwBwM9bj9XqxhmVcKmy+rDsOHGJm+ZsoP/MXxn42hqS03PZfSqdtYdSHS73VIZt7JSmfpV34Da2bk3D8eMByFi+3OHPEKJO0HhzKgmLqJa3fjnktq0sZzPMnEnPxVwgHW89wdWXNS/eeYrb5m6kwKryzp3dGNqhGS0a+RHRyJduEY6PIvvsyM4AfLLmCKfTLpe7XvbGjezv0JFLX39tfy6EcB3pdCuq5XyWWesQyrVop60/QUp6LpGNS08yJ+qnohaWP06lA9A9ogE3dglldLeqXUbcXn+ZPwG9auHI6Us0Tj2JMSqqVL+tpL/cX+J5o4kTq/R5QrgrrQ9OpYVFVMvfrm0LwKlLORpHUj5JVjzD1X1YXrgpmklxkSzedZqHvtjuVFmpmbksT0zmxM+/8ueI6wFonJtBw8/f59jNozk3Zw6Zv/5KwaVLZb5fZzLJ0Pqi3nCX0/6SsIhqKTpqHfOB+zV/t2riT6smkqx4iit9WGxbV71O4c4+hUPhXzX2SmXe/uUwj3y9k4PPvWhflq/zwvDDYgAuzP0Ppx59jMNx/Tj/4UdYMjMJ/+B9+7rWjAyOXDeC3EOHqlEjIURxkrCIamnbzDYyRWqm2T6zsju4kGXm2PlsYsKDtA5F1LLiR4NFc0kdSMkk3+L4VTtFc2QtbjvYvuyBvT/YHzefNZPw994F4Nzbb3Oodx8KLlygzc8rrhRSUEDuvn1VqYIQogySsIhq+3RSLwBW7EnROJIrthy7CMCy3WdktFsPUdb59aFvrrM/dqZVu+mxA8xZ8zaTE74r9VrHA/sJGj2awGHDiFr/GyEvTQMg5YV/kVc4KzNAxMcf0+CWW5z4VCHclJucE5JOtw5S3eP7cktdClsxHvtmJ8Oir8foBvP3XN8phKeHt+O9NUd46tsE5t7TU+uQ6oR0czq/Jv3K9rPbOZZ+jMy8THy9fAkPDKdb024MjxxOaECo1mGWqaJpIubc1R0vJybCvP30ZnLSyx4oruDSJbwa2q4y8mralIZjx2K68UYO9erNyb8+DEDrn37E2Lq1kzUQQlREEhZRbU0DjLx6axemLklkacIZxvaK0DokdDqFJ4ZGkXE5n1X7z2odjttLN6fzn93/4btD32G2mIluHE1UwyhM3iZyCnI4nn6cd3a+w5s73mR45HAm95hMRKD233NxRS0sL32/D1WFL+7vQ4eQQE5duszNXZs7VVbDESPIuWoclYQmbfG5ZwIdG5a+JFrn70+DcePIP3UKfeNGeEe417+NEK6ganyZkCQsDpIGlvIpisLdfVvw9ZYTfLr+GLf3CHebuXuOX8h26sjaE206s4kp66eQa8nlvs73cUe7O2jq17TUetn52fx49Ec+TvyYW5feyj97/ZOx7ce6zbQMQb4G4MrpwA4vrMBLp/DF/WXPsFwR0/Uj0H38MRcXLODU+UwWWYJZFDWEL4eWXZaiKIROe7HKsQvhztzjL1wSFuFCjwxpw+Pf7OL4hWxaN61smrialX45n+3HL7JqfyovjorWNBZ3tuTwEl7c9CKxobG83P9lmvk1K3ddf4M/Y9uP5abWN/HWjrd4ZcsrHE0/yv/1+T+3SFpaNvFn+/PDaOTnzQdrj5BwMp17YlvQr02TKpUXMHAAAQMHEGqxcvdzy2kfHMjAqNKJnBCidkjCIlxmw+HzAFi1Hl0I6DptJQCRjf24q28LjaNxTz8d/Yl/bfwXY9uNZWrfqeh1jvU98jP48Xzs80Q1iOKVLa9g1Bt5utfTNRytY5oEGAF4/Nool5XppVPQKTCxX6TLyhSiTtH+eASQq4Qc4ibflVtLzcxl4Y5ThJh8aNFI27FPsswF9scLHox1i07A7ubAxQO88PsLjGo9iudjn3c4WSluXIdxPNv7WT7f+zk/HP2h8jfUURm5BVhV2FZ4qkkIT5Ofa7vS8sh2x+fgqgmSsAiXOHEhB4tV5c2xXe1jX2glwOjFXX0i0Ckw/cf9JRIYAfmWfKasn0KroFa82O/Fap3OGd9xPDe1vonpm6eTku0+l7W70rRlewEYGeNcx10h6gu9wbZNb9pC21P9Tu1Z5s6dS0xMDCaTCZPJRFxcHMuL9aQ/e/Ys9957L82bN8fPz4/rr7+ew4cPV1jmvHnzUBSl1C0317mRKYW2jIVJio/BPVozZoyJ4ZVbuvBjYjILt5/UOhy3En8wnqPpR5k+YDreeu9qlaUoClP6TsFb783snbNdE6ATcvMtnE677NSgcM5Yf/gci3ed5l83RTM8OrhGPkMId6cv3L6bmvhqGodTCUt4eDgzZ85k+/btbN++nWuvvZbRo0ezd+9eVFXllltu4ejRoyxdupRdu3YRGRnJsGHDyM7OrrBck8lEcnJyiZuPj0+1KiZqV8vCIfAXbE3SOJIr7u7bAqOXDjcagFdzuQW5fPzHx9za9lbaN2rvkjJN3iYe6/YYPx79kaPpR11SpqMemL+d/jN/5clvEypcLzffUqVLMrccvUiTAG/u69+yagEKUR8UNsJq3T3RqU63o0aNKvF8+vTpzJ07l82bN2MwGNi8eTN79uyhU6dOAHzwwQc0a9aMBQsW8MADD5RbrqIohISEVCF84S5MPgYa+BkI9HGvftzeXjo2HD7H8I7BvPnLQfQ6hU7Ng7i+cwhhDbQ9WtDCD0d/ID0vnfu73F/5yk64pe0t/Gf3f/h639e8EPeCS8suS1pOHnkWK8nplwG4mJVX7rqJp9IZ9d4GfAw6Pru3N3GtG5c4DWa1qigKZZ4aO3o+i1ZN/N3iKightOIuv/4qdzawWCzEx8eTnZ1NXFwcZrMZoETLiF6vx9vbmw0bNlRYVlZWFpGRkYSHh3PTTTexa9euSj/fbDaTkZFR4ia0Y7WqpOXkE2xyr5axyUOjWHPwHINeX8PPe1PYdyaD11Yc4No31vLrAc8bUG7Zn8uIax7n8kHfvPXe3NL2FpYfX47ZYnZp2cX9/b+7afl/P9LtpV/oM301f56ztd4WjXJ7tdx8C6Pes21/8i0qd3+8hYmfbWXh9pP2GcbHfbSJVlN+Iq+g5Gklq1XlQHImgT6GGquPEHVCUcaicROL0wlLYmIiAQEBGI1GHn74YZYsWUJ0dDQdOnQgMjKSKVOmcOnSJfLy8pg5cyYpKSkkJyeXW16HDh2YN28ey5YtY8GCBfj4+NC/f/9K+77MmDGDoKAg+y1CRpbUTEp6LvfP3wbAzOUH3GoSxAcGtubZ6zswMKoJa/9xDSueHMSOF4bTq2VDHv16J1uOXuDw2UwST6XX+8655y+fZ1fqLm5sdWONlH9DqxvIzMtke8r2Gik/N9/Cop2n7M8/mtCTTyf14toOzdh89CLZZXx/7/16xP740Cs3MHNMF1IzzDyz6A8GzFpDr1d+YdvxSwAcTs20r5tXYGVfcgZHz2dzS/ewGqmPEHVF0QzoWm/ZnW6/b9++PQkJCaSlpbFo0SImTZrEunXriI6OZtGiRdx///00atQIvV7PsGHDuOGGGyosLzY2ltjYWPvz/v3706NHD959913mzJlT7vumTJnC009fGfshIyNDkhaNHE7NZM3BcwDc268lVlVF7zaNiLYB7R4Z0sb+PMDoxRt3dGXip1sZ99Fm+3KdAmv+MYTIxtpell1TtiZvBaBf8341Un7bBm1p5teMTWc20T+sv8vLLyiWCIc39CWysT/tQwI5ei6bXw+ksud0On1bNy7xnuKnKB/9egfTb+3CnX1acCk7jw1HzrP7ZBqfbDgGgK7wtM/Pe1P465c77J8zopN0thUerqhpQ+OMxekWFm9vb9q2bUuvXr2YMWMGXbt25Z133gGgZ8+e9mQmOTmZFStWcOHCBVq1auV4QDodvXv3rrSFxWg02q9WKroJbQxo24ToUBON/b35103RGOrAUPihQb4snzyQ12+P4bN7ezGySyhWFQa/vpZV++rnqaI9F/YQHhBOE9+qjfxaGUVR6Nq0K3su7KmR8gOMXhyfOZLFj/YjwOjFfZ9v5WJ2nv3qnbIa9v46uA0HX7mehwe34ee9Z5n2/T4AGvp7M6prc56/KZo5d3UHYPT7vzPq3Q32ZOWfI9qz7PEBMo6P8HhXzgjV8bmEVFW1918pEhRkm7338OHDbN++nZdfftmp8hISEujSpUt1QxMuYC6w0P75FQAMad+UdsGB5BVYKbBa8dLp2JecQUp6LkkXbf0B3GUOofK8tuIAPgY9OgVW7U/l+IVscvIsJfovuMNIvTXhaNpRohq6bgTYsrRr2I6v939do5/Ro0VD3rijKze9u4HFO0/Z+02V14/F6KXn2evbs+d0OtuOXST9cr593iGAm7s2p0NIIL8dOseCrUn4GHT89MRAzaeXEMJtFLY+ar1pdCphmTp1KjfccAMRERFkZmYSHx/P2rVrWbHCtkNbuHAhTZs2pUWLFiQmJjJ58mRuueUWrrvuOnsZEydOJCwsjBkzZgAwbdo0YmNjiYqKIiMjgzlz5pCQkMD777/vwmqKqvp225UxTNYePEfShRwMeh16nYK5wIKqQotGfiRdzKkTl35+sPZPAHwNeoZ2bMbw6GACjF408DNgVVUuZOUxqF39nC8mOTuZuOZxNfoZYQFhpJnTuFxwGV+vmrsKKzrURI8WDXj954M08LMlH//bdbrMeYOsVpUPfzvKhew8UjJymbokkffv7lFinXbBgbQLDuSBga1rLGYh6ip3OQx1KmE5e/YsEyZMIDk5maCgIGJiYlixYgXDhw8HIDk5maeffpqzZ88SGhrKxIkTeeGFkpc4JiUlodNdOWWQlpbGQw89REpKCkFBQXTv3p3ffvuNPn2cn2G1xtTPA+5KqarKwu22To47nh9G48J5Wspisaro3bx1BeC122N45rs/mH1nN0Z08qxL6TPyMmhgbFCjn+Hn5QdAWm4avgE1l7DodArPjezIbXM30bKxP2czzPx3+yk6hwUxITYSc4GV++dv4/cjF+zvaRJgpIGfwSMvZxeiWuznhDSNwrmE5dNPP63w9SeeeIInnniiwnXWrl1b4vnbb7/N22+/7UwYopYs3nmaxNPpvHtX9wqTFaBOJCsAd/QMZ9GOU7z6036iQ01ENPLTOqRaY7aYMeor/h6r69ClQwAcSTtCaEBojX5W/NaTNPb35t27uoMC17y+ln8t3cuBlExW7j3L+Swz3l468gqsvH57DLf3DJfxVISoAsV+SqiOXdYsPMPhs5n8e9lexvQIY1TX+jOHiqIoTL+1M+mX8xn0+hq2H/ecCe0MOgP51vwa/YwWJtvM2OGB4TX6OQC/7D/LHb0iaGbyoVmgDxuevZYRnYL5ZksS57PM3NuvJYdeuYHjM0dyR68ISVaEqOMkYRGlHDqbyfC3f6OBn4EXb+6kdTgu17ZZIN8/PgBVhYcKrwjxBAGGADLMNTvAok4pnCTNt+b7AZl8DHy56Tj7ztjq1NDfm7nje/LRhJ7847p2PDW8XY3HIISnUBTtO91KwiJK2HL0And/bBubZPLQKEz1dJTP0CDblSUXs/Pq/YBxRUL8Q0jJqdkZlZOzk/E3+BPgXfNX2Cx9rD/ZeRZunLOeT9YfJTffgk6ncF2nEB6/NqrElUBCiGpyg4zFvSZ+8SCqqmKxqhQU3SxWCqwqqmq/ggwF2ymMooZsRSkccVAp/ryMssv8vMpXOnExm3EfbSaqWQDfPdzPPqFhfeSl1/HiqGhe/H4fe0+n0yksCB8vHV51YAyZqmppasnO1J01+hlHLh2hlcnxcZeqo6G/N9Nu7sRHvx3llR/388qP+1nzjyG0qse/WyG0oqB5viIJixYmx+9iacIZrcMoU7NAI4se7VdvW1aKG94phBe/32cf7TbI18Duf19XybvqrujG0Xx3+Duy8rJqrAUk8XwifUJq7wq/Sf1aMqlfS/actk1wOOaD31n99yE08veutRiE8Ahu0AVMEpZalmUuYNnuMwyPDmZ4dDAGvYKXTodBr6BTlBK9sVWKZ7S21peip7bHJVtkiihX/bJKv17+az1aNPSIZAUgrIEvX97fh/TL+Tz+zS7SL9dsh1St9Qntg1W1siVlC0NbDHV5+clZyRzPOM7fuv/N5WVXpnNYEEsf68/N7/1O0sUcSViEcDXtzwhJwlLbDp3NtHX2HNSa3i0baR2OxxsYZescmpKeyys/7kdV1Xp7NUlEYARtgtqw8vjKGklYVp5YibfOm9jmsZWvXAO8vWyn87S+9FKI+sh2ICyXNXuM3HwLUxcn0qqJP13CgrQORxRTdER+zRtr+fVA/ZxLCOCmNjexOmk1l3IvubRcq2pl8eHFDIkYgslbm3m93GVGWSHqJTdoYZGEpRb98EcyB89m8sH4HvgYZEI1dzK4XVMeHdKG4xdySDxVs5f+aun2qNvRKTqXz/ez9uRajqYf5Z7oe1xarjOKGsakhUUI11O0b2CRhKU2/bIvhW4RDegYKjNLu5vGAUb75c0Gr/p5SgiggU8D7mx/J1/s+4KUbNdc4pxvzeftHW/TJ6QP3Zt1d0mZVXFlRlnNQhCi/lIUzQ8GJGFxgKt2Xycu5Eiy4sYiG9suhx3aIVjjSGrWgzEP4uflx7RN01yyAfpw94ecyjzFM72fcUF0VVc0U7jFKhmLEK7mDodxkrA4ygUdMU0+Bi5kmV0QjKgJgwtnaf7hD/e85NxVAr0Dean/S2w4vYFPEj+pVlm/nfqNjxM/5q9d/0r7Ru1dFGHVGAs73eZZrJrGIUS9JH1YPIuiQOKpdDkCdFPrDp0DoENI/W8FGxQ+iEe6PsKcXXOIPxBfpTK2Jm/lH+v+weDwwTzY5UEXR+i8oquE8gokYRHC1RSQPix1gav6Gj09vB1n0nN5bkkin6w/yp7T6S4oVbiCqqq88fNBwhr4MjKmZmcZdhePdH2Eezrew/Qt03l92+vkWxwbh0ZVVRYeWsjDqx6me7PuzBo0C71O+07kusJWUDkeEKIGKAqqxhmLjMPiCBWXnMDr27oxz4/syDurD5OZW0DX8CCWPj6g+gWLalMUhf5tm7D3jOckkYqi8EzvZwgLCOPN7W+y/vR6JnefzDUtrrFPYni1hNQE3tv1HltStjC23Vie7fMs3nr3GKTNXNiyUnRqSAjhOu5wlZAkLLXsgYGteWBga1743x52nHDtWBiiepqZjKzan8uFLDONA4xah1MrFEXhnuh76BPah1lbZ/Hk2idp6tuUAWEDiGoYhcnbxOWCyxxLP8bm5M0cTT9Kq6BWzB02lwFhrk+2LVaV1fvP0iU8iNAgX6feW3QqyFCP54MSwpNJwuIA2ySEri0zIzcfvc4d+l2LIqNimvPNliQ++u0oU27sqHU4tapdw3Z8OuJTEs8l8tOxn9h+djs/Hv2RPGseekVPRGAEXZt25e+9/s6AsAHltsBU12cbjjH9p/0ABBq9ePq6dozrHYGft+Obqno6ULEQmlLc4LJmSVg0cC7TzNKEM0TLJc5uJa5NYx4c2IpvtiTxt6FRBBg978+jS9MudGnaxf48z5KHQWeolekKLmXn8frPBxkY1YSbuzZnxvIDvPTDPj5cd5Qv7u9Du+DAGo9BCFEOuUqojlBx6WHbhWzbpc1/HdzaZWUK1xjbK4JMcwFfbT6hdShuwVvvXWtzKxkNOiyqyo1dQrmjVwQ7XxjO2n8MweTrxcg56/kpMblW4hBClOYOfVgkYXGAYv+faxRYbN966yYBritUuERUcCCtmvhzILn+Ds/vrvy8vWjRyI9DZzPtyyIb+7Ps8QEMad+MyfG7+GLTce0CFEJoShKWWqaqKje9uwEAX2/tLwUVpXUOC2Ljnxc4XGzHKWpHdHMTO5PSSizzMeh5c2xXRncL419L9zJj+X4OpEhCKUTtk6H53Z4rW1iKjxER0ci5qyBE7RjaoRmpmWZu/88mcvIKtA7Howzr2IzdJ9M4fj67xHKTj4HXb49hYlwkH647ys3v/c7Pe10zF5IQwgGKIn1YPI1ep/DPEbYhzCd+upWTF3M0jkhc7ZbuYSyfPJD0y/n8Vjj6ragdN3QOpZG/N19sKt2HSFEUXhrdmb3TRtC7ZUP++uUOdiXJ0ABC1AZ3uPhOEhZHqLi04+Fj17Tl3bu6sz85gxveWc/C7Sc1v1xMlNQ+OJABbZvwj4V/lDraFzXHx6Dn5q7NWbGn/A62/kYvXh7dmRaN/Pj7f3ez8ch5Nv55noSTkrwIUWPcIGPxvOs23UBOXgELd5wiI9d2uuGf3/3BP7/7gz3TRnjkpbS1wWpV+e3wObLMZZ/iKStfvCkmlA1HznPfvG2s+ceQmg1Q2AWbfMjJt1S4TuumATw/siMPfbmDuz/ZUuI1k4+hJsMTwmNpfVwte0cHuHrguOh//Vzm8oSkNAZENXHdBwm7TzYc5dWfDlTpvemX81FVtdYu7/VkyemXWXMgFS8HBlW8rlMIm6ZcS16BFVW1dQf0MeicHiFXCFE52+SHMnBcneDszspcYGHTnxfIMhcwrGMwPobSVwRtfW4oF7PzOJ+ZRyN/b6Kby0ByNSWqmW3QsXn39aZXy0ZlrlPeN+ztpZNkpZbM+/04W49f5NVbu1S+MkhyIkRtURSth2GRhMUxjh1d7z2TzpTFiegUhYSTafbl0aEmfpo80P48xORDSkYuf/1yB0se7Q8hNRGzKK5TmC0Z3Hb8IkPaN9M4GlGeqMLRbGf8tJ9txy/y9rhu2gYkhADcY8oL6XTrAEWFlIxcliacxlrB3PU/7z3LH6fS2Z+cwW09wln8aD/u6tOCfckZJRKYn58aBMCupDQu51V8rl64RmZhf6FOzYM0jkRU5Pae4Sx6pB8xEUF8v/uM1uEIIYqTPix1w+HULBbEJ/D15iQeGdKGazpcOUq/lJ3HR+uP8uv+VAB+fGIgbZvZRrHtEhbEgq1JvPfrYcb0CCclPRdLYdLTM7KhDB5XS4q+m2ukdcXt9YxsyPCOwWw/Llf9CCGukITFAT5eem7q2pThrf35YO2f3DdvGwBfP9CXpoFGrnv7NwC6RTTg83t725MVsE11/5f+rfhi03FWFe40i3wysVftVcLDFQ3St/X4RQa3a6pxNKIyBVYVg14agIVwGwqaD7/h1BZh7ty5xMTEYDKZMJlMxMXFsXz5cvvrZ8+e5d5776V58+b4+flx/fXXc/jw4UrLXbRoEdHR0RiNRqKjo1myZInzNalBOp1C9xYN+evgNiT8azh39o4AYPwnW+zJys9PDuJ/j/Uv0fJS5F+jotn63DAWP9qP9c9cw7cPxbLiyYE09Peu1Xp4ssHtbN/LmbTLJZbn5ls4l2nWIiRRgTyLFS+9G5w0F0IAoLjBQCxOtbCEh4czc+ZM2rZtC8D8+fMZPXo0u3btIjo6mltuuQWDwcDSpUsxmUy89dZbDBs2jH379uHv719mmZs2bWLcuHG8/PLL3HrrrSxZsoSxY8eyYcMG+vbtW/0aukKxrFJRFHKK9Tu5sUsI10WH0D4ksMIiGvl706gwQYlo5FczcYpy+Rh0BBq9eP5/e/gpMZnrooP5YtMJDqdmATC4XVM+u7c3egcupxU1r8Ci4qWTFhYh3Epd6sMyatSoEs+nT5/O3Llz2bx5MwaDgc2bN7Nnzx46deoEwAcffECzZs1YsGABDzzwQJllzp49m+HDhzNlyhQApkyZwrp165g9ezYLFiyoSp1cTlVBKbbt/OeI9kQ1C6BPq0b0bd1Yu8CEwxRF4cOJPVm04zQ/JSaz/vB52gUHMGNMF1LSc3ln9WG2HL1Av7YyDo47KLBYMUgLixDuQ9E8X6l6HxaLxcLChQvJzs4mLi4Os9nWrO7j42NfR6/X4+3tzYYNG8pNWDZt2sRTTz1VYtmIESOYPXt2hZ9vNpvtnwmQkVGDs7eqUHyUjohGfvxtaFTNfZ6oEf3aNKFfmybMuq0LCSfTiG5uws/bC6tV5avNJ1i2+4wkLG5Cp1PIMhdwMTvP3jIphNCOoqB5xuJ0m2tiYiIBAQEYjUYefvhhlixZQnR0NB06dCAyMpIpU6Zw6dIl8vLymDlzJikpKSQnlz8vSEpKCsHBwSWWBQcHk5JS8UysM2bMICgoyH6LiIhwtioOU1Hd4hp04Rpeeh29WjbCz9uWr+t0Co9d05b4bSdp+X8/0uXfPzPq3Q0sTTitcaSe6+auzfHW67j7481cyJI+RkKIKiQs7du3JyEhgc2bN/PII48wadIk9u3bh8FgYNGiRRw6dIhGjRrh5+fH2rVrueGGG9DrK7509+pB2RwZBn3KlCmkp6fbbydPnnS2Ko7Tuh1M1Lh7+7XkjTu68pf+rejZsiGJp9NZue+s1mF5rNZNA4h/KJbzWXk89s1OrcMRQgBa7wydPiXk7e1t73Tbq1cvtm3bxjvvvMOHH35Iz549SUhIID09nby8PJo2bUrfvn3p1av8y3dDQkJKtaakpqaWanW5mtFoxGg0Oht+ldj6sEgTS32m0ync3jMcetqed/rXCqJDZaoELUUFBxISZKShn5wSEkJziqL1VELVH+lWVdUSfUkAgoKCaNq0KYcPH2b79u2MHj263PfHxcXxyy+/lFi2cuVK+vXrV93QXEfrb0nUqtx8C9l5Fkw+MkyRljJz89lzOgOLVdV8/AchPJ07HLI7tUWeOnUqN9xwAxEREWRmZhIfH8/atWtZsWIFAAsXLqRp06a0aNGCxMREJk+ezC233MJ1111nL2PixImEhYUxY8YMACZPnsygQYOYNWsWo0ePZunSpaxatYoNGza4sJrVo+Ie8yiI2rFij63FTzrgaivA6MVfB7fmw3VH2ZmURs/IhlqHJIRnq0stLGfPnmXChAm0b9+eoUOHsmXLFlasWMHw4cMBSE5OZsKECXTo0IEnnniCCRMmlLo0OSkpqUQn3H79+hEfH8/nn39OTEwM8+bN49tvv3WfMVgAVOdnaxZ11/6UDEJMPrRpGlD5yqLGKIrC34e3x+Tjxbu/HiYtJ0/rkITwXG5wWbOi1pO21oyMDIKCgkhPT8dkcl3fA1VV+eCRNVwzoQPR/Zu7rFzhviZ8ugWAL+93o6TZgy3YmsTUJYkYdDpu6xnO369rR5OA2um/JoSw+frfm2nZpTH9b3f9kB6O7r9lKMlKFM3OrJNOtx4hMzef3SfTaCGjEbuNu/q0YMuUoUweFsXyPck88tUOLmVLa4sQnkYSlkpYLYUJi4y66RF+P3KejNwC7u7bQutQRDHNTD48dk1bPpnYi90n04mbuZo9p9O1DksIj6L16RhJWCpxJWGRfypPcPLiZXwNejqEyCXN7qhXy0as/vtgACZ+tpUP1h7hSOF8UEKImlMnR7r1NNYCKyAtLJ7i+IVsWjbxl0kQ3VhEIz8+GN+DXpENmbP6MMPeWsfuk2lahyVE/VeXJj/0RHJKyLNk5hZoHYJwwLUdgrm2QzA5eQVE/+tnJn2+lXv6RtLAzwDAiQs5bD9xCZOPF/8e1Yno5tJiJkS1uMGVstLCUgmLxdbCopdTQh4h32Jlf3IGBYXfu3Bvft5evHxLZ0w+BuK3neSNlQd5/eeD/P7neTqGBLLl2EXmrD6sdZhC1AtqXRua39NYC6SFxZPc0Suc5XtSOJCSSeewIK3DEQ6YEBvJhNjIMl+7IFcTCeES0oelDpBTQp5l54k0fA16WjSWy5rrA71OwVI/hpoSQnNa/yVJwlKJonH1ZPLD+m9X0iXeW3OE23qGYfIxaB2OcAGdotjHUhJCVJ0bdGGRhKUy9oTFHb4tUaNeW3EQgCk3dNQ4EuEqeh3SwiKEq8gpIfdWtK1T5F+q3jt2PhtALpGtR/Q6BYu0sAjhAsqVHaJGZDdcGdnWeYybu9nmiuoknW3rDZ2iYJUWFiGqzw1OMkjCUgk5JeQ5DHqFsAa+BPlK/5X6QlpYhHAdrf+SJGGphP3gTPKVek8nSWm9o1cUrDKkjhDVJpc11wVFfVhkZ1bvKSCnD+oZnVzWLITLaP2XJAlLJYpG9pN8pf5TFEXrPmXCxfSKnBISwhXc4aBdEpbKyLbOYyiKtLDUNzrpwyKE62i8fZSh+Suhyikhj6GgSH5az3jpFPItVrLMBSjYklIFBUUBH4Ne6/CEqFO03j5KwlIJ1Z6xaBuHqHkqKucyzazYk8Kwjs3wkgkv6zwfg842L9S/fy712tQbO/DQoDYaRCVE3eMOnW4lYamMvYVF2zBEzSs64n74qx3c1SeCGWNiNI5IVNfDg9vQNaIBqmr7Uy46AHnp+31cyJKJEYWoSyRhqYSMw+I57u3XkqEdmrHmYCqzVhzk6eHtaRpo1DosUQ2NA4zcFNO81PKXf9iPv1E2f0I4RUa6dXMyDovH8DHoiQoO5OauYVisKpuOXtA6JFEDLFaVi9lmGgd4ax2KEHWHon0fP0lYKmHPVyRh8RghQT7Etm7EaysOcCHLrHU4wsVs4+3A9B/389ySRK3DEaJOcIc+LJKwVEJOCXmmN+7oyuU8C88uSuTouSxOXMi+0gFb1Gk6ncKMMV0weun4eksSF7OlL4sQdYEkLJWRfZRHCm/ox7COwazaf5Zr31zH4NfX8lNiitZhCRe5q08Lbu0eDoDJR/qyCOEIrXeH8pdaCbms2XM9OTyKfm0b0yzQh38t3cM7qw9xbYdm+HrL+B31waWcPNo2C5DL14VwgO2UkHS6dW8ycJzHCg3yZXS3MOLaNGb2nd04efEyj3+zk9x8i9ahCRdYsus0A6OaaB2GEHWE9vtASVgqIZ1uBUCn5kHMvacH6w+fZ+Sc9azYk8Kf57LIK5CpgOui84WdqdsHB2ociRB1iHS6dW+qVTrdCpsh7Zvx4xMD8Dd68fBXOxj65jq5yqSO+vz3YwBc27GZxpEIUTcoiub5iiQsDpN8RQBRwYH879H+rH/mGvq1acySXafJySvQOizhpKzcArz1OpoF+mgdihB1g1zW7P5k8kNxNZ1OIaKRHzPHxFBgVfn89+NahySccOhsJgu2nmRCXKTWoQghnOBUwjJ37lxiYmIwmUyYTCbi4uJYvny5/fWsrCwef/xxwsPD8fX1pWPHjsydO7fCMufNm4eiKKVuubm5VauRq8nYG6IcEY18aeBn4EzaZa1DEU74ZP1RmgR488z17bUORYg6RdW4icWpy5rDw8OZOXMmbdu2BWD+/PmMHj2aXbt20alTJ5566inWrFnDV199RcuWLVm5ciWPPvoozZs3Z/To0eWWazKZOHjwYIllPj7u0VRrb2GRtiiB7TL3pIs57Ey6xH+3nSItJ58OIdJxs65Iz8lnacIZnhgahdFLLk8XwlGKG3RicSphGTVqVInn06dPZ+7cuWzevJlOnTqxadMmJk2axJAhQwB46KGH+PDDD9m+fXuFCYuiKISEhDgffW2wD8Mip4Q83a6kSzzy1U5SMmytf+2DA/n8vt5c0146btYVm45ewFxg5cYuoVqHIkSdo/UJhyq3G1gsFuLj48nOziYuLg6AAQMGsGzZMk6fPo2qqqxZs4ZDhw4xYsSICsvKysoiMjKS8PBwbrrpJnbt2lXp55vNZjIyMkrcaoKKDBwnbN765RC+3no+v7c3Cf8azs9PDZJkpY6JDjUBcPhsJmfSLst0C0I4yB26cTo90m1iYiJxcXHk5uYSEBDAkiVLiI6OBmDOnDk8+OCDhIeH4+XlhU6n45NPPmHAgAHlltehQwfmzZtHly5dyMjI4J133qF///7s3r2bqKioct83Y8YMpk2b5mz4TlMLh9lwhy9LaGPVvrP8ejCVDUfO8+iQNlzTQZKUuqqhvwGAh77cYV+264XhNPSXmZuFcHdOJyzt27cnISGBtLQ0Fi1axKRJk1i3bh3R0dHMmTOHzZs3s2zZMiIjI/ntt9949NFHCQ0NZdiwYWWWFxsbS2xsrP15//796dGjB++++y5z5swpN44pU6bw9NNP259nZGQQERHhbHUcJxmLR8rMzeeBL7YDcG2HZjx+TflJtHB/gT4G3r+7B8t2n+bnvWcBuO0/Gzl+PpubuzYnKjiQBwa2kv4tQlzNDYbmdzph8fb2tne67dWrF9u2beOdd95h9uzZTJ06lSVLljBy5EgAYmJiSEhI4I033ig3YbmaTqejd+/eHD58uML1jEYjRqPR2fCddmW25hr/KOGGzhb2V3nt9hjG9qrBhFjUmpExoYyMCeXaN9Zy9Hw2R89lA/C/hDMAvP7zQRY/2o9OzU2SuAhhp2jd57b6kx+qqorZbCY/P5/8/Hx0upLdYvR6PVar48OXq6pKQkICXbp0qW5orqH1NyQ0FdHID4ACi/wQ6ptv/xqHucDC3jMZDGjbhJw8C72nrwJgzAcb+fvwdvxtqLSoCQHucdDuVMIydepUbrjhBiIiIsjMzCQ+Pp61a9eyYsUKTCYTgwcP5p///Ce+vr5ERkaybt06vvjiC9566y17GRMnTiQsLIwZM2YAMG3aNGJjY4mKiiIjI4M5c+aQkJDA+++/79qaVpG9hUXnBt+WqHVGLz1dw4P497I99GnVkLbN5BLm+qJpoK2FNryhLSn1N3pxZPoNJF3MYcKnW7mUk69leEK4n7p0WfPZs2eZMGECycnJBAUFERMTw4oVKxg+fDgA8fHxTJkyhfHjx3Px4kUiIyOZPn06Dz/8sL2MpKSkEq0waWlpPPTQQ6SkpBAUFET37t357bff6NOnj4uqWD2qXCTk8d4a142HvtjOPZ9s5dkb2jO6axg6SWDrJS+9jtZNA2jTLIDPfj9G+5AAxvVuoXVYQrgFrS+qU9R6cl1fRkYGQUFBpKenYzKZXFbuwS0prPp8Hw+/OwS9QUaP81TJ6Zd55rs/WH/4PA8PbsP/3dBB65BEDbqQZebOjzbjpdexfPJArcMRQnPL3tmFt68X1z/k+u4aju6/ZQ9cCVWaWAQQGuTLl/f3ZUJsJB/+9ienZTj+eq1xgJG7+rTgQEoGGblyakgId5iuWRKWyhR9QZKwCOD2nuGoKqTl5Gkdiqhh13RohqrCqHc3cN/nW+n0rxW0mvIjx89nax2aELXOHXaBkrBU4splze7wdQmt6Qp/B/XjRKqoSKsm/gyMasKJCzmsOXgOL70OVYXhb6/jHwt3s3jnKa1DFKL2aN/AUv3Lmus7OSMkiivKWyVh8Qxf3t+XzNx8VMDkYyDbXMDz/9vDdztO8d2OU6w5eI537+qudZhC1A45JVRHSMYiuNLCYpWMxWME+hgw+diG9Pc3evH2uG4cnn4Dt3Rrzve7z7D2YKrGEQpRGxTN596ShKUSqlVOCYkr7C0s2oYhNGbQ63h7XDdiWzfipR/2YbHKL0LUb+6wC5SExQHu8EUJ9yAtLKKIoij87doojp7L5pnv/tA6HCFqlhvsByVhqYSqIhmLsNNJHxZRTP+2TQgN8pFNhKj33GDuQ0lYKqWqsjESdlc63UrGImxCg3zc4eBTiHpPEpZK2FpYtI5CuAvFfkpI40CE21AU7WexFaLGKYrmTSySsFRCVUGRjEUUKvolSAuLKOIOTeVCeAJJWColWyJxhU5aWMRVbCOWyw9C1G9uMDK/DBxXGZ8AA5YCK3mXC/D2lX8uT2cf6VbzP11Rmy5m53EkNQuwta6p2FpVVFQycwu035ILURs0/p3LHrgSgY18Aci8mEvjsACNoxFak5FuPdM/Fu7m1wPlDxAX27pxLUYjhDa03u5JwlKJwEZGQBIWUZLWf7iiduXkFXBth2Y8N7IjCraOtrZ7Wx+35g18tA5RiBplu+DAqmkMkrBUwi/IiE6nkHUxV+tQhBsoSlR00g/boygo+Bu9aNNUDlqEh3KDbZ50uq2ETqfg39BI5kWz1qEIN2Dvu+IGf7yi9tiu6JRmNeG5FNC8D4skLA4IbORDprSwCIrP3i0ZiydxhyskhNCUG/wNSMLigIBGRjklJIArf7BySsizKO6wtRZCazJwnPuTFhZRpGjSQ5m927PIWCtCKFrnK5KwOCKwkQ/ZaWYsFm17SAvt2U8JSb7icbTeWAuhJXfY5slVQg7w9dOhqpD320f4+liu2nIVPi5rWanlhezfvFLsuVL2a6XKL+f5lcKvlFfivthrOi/Q6cuo6VW/yDJ/ocWWGXwhejToDWWsV18VtrBoHIWoXYqi/dGlEJpyg42eJCyOSDsBgLr+bfDKvrK8xA5dKfNh6QVqiTtQy0lGis26WGaCU/x58bdfVUaJ+8LXLXnlJ1jO+nkq/G0HGAOrXkYdcqWFxQ3+ekWtUZBTQsKzucOcWZKwOEDBYnswYQm0itY2GC0V/7WqVph/M5zYAJdOQEhn7eKqRVZ7wqJtHKJ2ucFEtUK4Ael06/auzNCraRjaU5QrN50ehr9kW37kF0j8DvYsghObtI2xhqlySsgj2VpYhPBgbnCUJi0sjtD+e3JP/k1A7w2rXryyTNHB1GQw1M+hyq+MdCs/Ck8ifViEQPOsXRIWZ8gGq6SGkTDlFFjyAdXWwvL9ZLfIxGuKXCXkmeTrFp7OHU6LSsLiAJmhtwJeRtsN4M9fbfe6+v+zkt+CZ1HcYVxyIbTkBlm79GFxgBxVO8i/me2+zEum6wdd4V+MVTIWDyOnhITQej4tSVgcUfQdScJSsUatwOCndRQ1qqjviuy7PIvMJSQ8nTvMnyYJiwNUGY7dMb4NIT8HzJlaR1JjrlwxJrsvT2Ibg0K+c+HB3GD351TCMnfuXGJiYjCZTJhMJuLi4li+fLn99aysLB5//HHCw8Px9fWlY8eOzJ07t9JyFy1aRHR0NEajkejoaJYsWeJ8TWqQnBJyUFqS7T7jjLZx1KCipNUq+y6PIi0swtO5QzcupxKW8PBwZs6cyfbt29m+fTvXXnsto0ePZu/evQA89dRTrFixgq+++or9+/fz1FNP8be//Y2lS5eWW+amTZsYN24cEyZMYPfu3UyYMIGxY8eyZcuW6tVM1L4jq233jaO0jaMGSQdsz6RIHxbh6dzgKiGnEpZRo0Zx44030q5dO9q1a8f06dMJCAhg8+bNgC35mDRpEkOGDKFly5Y89NBDdO3ale3bt5db5uzZsxk+fDhTpkyhQ4cOTJkyhaFDhzJ79uxqVUxoIDDEdr93MexbdqXFpR7R2VtYZO/lSaSFRQjQ+q+gyn1YLBYL8fHxZGdnExcXB8CAAQNYtmwZp0+fRlVV1qxZw6FDhxgxYkS55WzatInrrruuxLIRI0awcePGCj/fbDaTkZFR4lZj5KjaMSPfhMDmsOh++O8EeLcnZCRrHZVL6Qp/C5KweBbbGBTynQsP5gZ9IpweMCMxMZG4uDhyc3MJCAhgyZIlREfb5teZM2cODz74IOHh4Xh5eaHT6fjkk08YMGBAueWlpKQQHBxcYllwcDApKSkVxjFjxgymTZvmbPhVov3XVEcENIPHt0H6KVg3y9bS8ulwaNoeAkLgupfBr5HWUVaLvae87Ls8ijtcISGEltxh8kOnW1jat29PQkICmzdv5pFHHmHSpEns27cPsCUsmzdvZtmyZezYsYM333yTRx99lFWrVlVY5tVX36iqWukVOVOmTCE9Pd1+O3nypLNVcZ4bZJhuzxgAzTrA8Gkw4lUI6wF6IyR8BatrJ8GsSUU/AbPFyn+3neR02mVtAxK1wqBXSEhKY9W+s1zOs2AusDj0vkvZeRxJzZTWGVH3ucHuz+kWFm9vb9q2bQtAr1692LZtG++88w6zZ89m6tSpLFmyhJEjRwIQExNDQkICb7zxBsOGDSuzvJCQkFKtKampqaVaXa5mNBoxGo3Ohl8lMvlhFTRoAXGP2W4Ay/8PtsyF9iMhanjZyV/WOVjxLORlg1I0+JwK7UZAz3trK/IKFYV93+fbAGge5MMrt3bmmy1JJF3MwUun44mhbbm+c6iGUQpXe2Bga/6XcIYHvrjSH+/du7ozqmvzUutezM7jwS+2s+PEpRLLn7m+PY8OaVvjsQpRE+pkC8vVVFXFbDaTn59Pfn4+Ol3JIvV6PVartdz3x8XF8csvv5RYtnLlSvr161fd0FzHDTLLOq//E2AMgm/ugM+uh5yLpdc5vcM2H9H5Q6BabLeDP9nmJ/p9ji2h0ZhBf+X3/c6d3Tifncdf5m3n0Nkswhr4si85g4e/2klmbr6GUQpX6xwWROKL1/HPEe0Z0cl2MPW3Bbv499I95OQVlFh39qpDpZIVgNdWHGTYW+u4lJ1XKzELUd841cIydepUbrjhBiIiIsjMzCQ+Pp61a9eyYsUKTCYTgwcP5p///Ce+vr5ERkaybt06vvjiC9566y17GRMnTiQsLIwZM2YAMHnyZAYNGsSsWbMYPXo0S5cuZdWqVWzYsMG1NRXaMjWH/zsBB5fDwkmw/k0YMb3kOkXNFxOWQMOWtscFZvjpH/DLC7B5LjyZCHrt5ipqFmjk3bu6MzCqCQ38vGng583moxd44toofL31bD9+kdv/s4nvdydzd98WmsUpXC/Qx8Bj19haSH744wxfb05i/qYT7DqZxowxXejUPAiA5XtSaOTvzbp/DiHA6EVaTj7XvrmWSzn5HEnN4lJOHg39vbWsihDOc4PZD51qYTl79iwTJkygffv2DB06lC1btrBixQqGDx8OQHx8PL1792b8+PFER0czc+ZMpk+fzsMPP2wvIykpieTkK1eO9OvXj/j4eD7//HNiYmKYN28e3377LX379nVRFYXbUBTocCPEPgo75kNeTsnXiyZRLMgruezmd6HnfZCVAmr5rXW1QVEURnVtTgM/2w5ncLumPHt9B3y9baewekY2ZHS35kz7fi87k0ofZYv64aaY5ix4KJYZY7pwMCWTkXM2cPx8Nhv/PM+5TDOX8ywE+hhQFIWG/t68Pa4bALNu60LrpgHaBi9EVbjBmQanDlU//fTTCl8PCQnh888/r3CdtWvXllp2++23c/vttzsTSi2Tzisu1ag15GVC+knbFURF0k/Z7i8dg6btSr5Htdpu+dng5b5Hp4qiMOu2GM6kXeaeT7bQsrE/HUNN9GvTmFu7h6HTucFfvXCZu/q0IDrUxNgPNzHkjbX25dNv7QxAtrmATv/+2b68X5smtR2iEC7hDn1YtGtbr4skb3ENS2ELirXA1sE28TvY9SWc2gYt4qDVoNLvGfAU7F4AWz6CIc/WbrxO8jHo+XhiLz77/Th/nEpj7cFUFu08xZ4z6fx7VCetwxMu1jWiAWv/OYRdSWm0aORHZGM/An0MAHy47k8AukU04M2xXYloVHJyUKtVJdNcQMblfNIv55NxOZ+2zQJoZvKp9XoIUSE3uEpWEhYHuMH3VL807w4+QTC3WMdqgz9E9oe7FoDBt/R7TM1tic7+ZW6fsAA08PPm6eFXWom+3HyCF/63hw4hgYztFcHxCzm0bOwnE2rWE6FBvoR2Kf27vZhjS86jm5t465dD9sQk/XI+aTn5ZObml5qXSqfAgKim3NYjjOuiQ+ynG4XwdJKwiNoX3gsm77a1liRthO4ToEslpwQP/mS77/e3mo+vBkyIjWTbsYtM+34fn204zsGzmTxzfXtGdAohyNdAk4DauURf1K6Y8AaENThH4ql0TL5eBPkaCG/oi8nXQFAZN3+jF1uPXWTxzlNMjk/A31vPDV1CGdMjjNhWjeWUotCMO8xYLgmLE+SMkAv5NnSupeTCEdt9UETNxFMLXh7dmcjGfhxJzSImPIjXVhzktRUHadPUn9V/H6J1eKIGjO0Vwdhezv1m2zQN4K4+LUi6kMOSXadZvOsU3+04RfMgH27tEcat3cNp20w67opa5ga5siQsom7o/QAc+Ml2ifMjG+vkebogPwN/v87WydhqVRnYrimfrj/KobNZGkcm3FGLxn5MHhbFE0PbsjPpEot2nubLTSd4f82fdA0PYkyPcEZ1bU4juURa1AJ36HRb7YHjhKgVvg2h7TBI3af5pc2uoNMp3Ny1OWN6hGPReisg3JqiKPSMbMSrt3Zh63PD+GB8D5oGGnn5h330mb6KB7/Yzoo9yQ5PFyBElbjBQaK0sIi6IzvVdm/OBN8GmobiKga9jrwCK32mr8Kg12H00uHtpcOgt90PjGrCk8PaVV6Q8Ag+Bj03dgnlxi6hXMgy8/3uMyzedZqHv9pJkK+BUV1DubV7OD1aNJAO3cL15LLmukQ2AJrqdg/smAdvdoAWfeHWDyEwROuoquWGziFkmfO5nGclz2Ih36KSV2Alz2Jlx/FLLEs4IwmLKFPjACP39m/Fvf1bcfhsJot3neZ/u07z1eYkWjXx5+auzXlwUGsCjLKZFy6ggNYZi/ySRd0R1hPumA+nt8MfC+GDWJj8B/iYtI6syhr6e/PQoDZlvjbjp/2s3He2liMSdVFUcCDPXt+Bf1zXns1HL3DPp1t4Z/VhIhv7MaZHuNbhiXpA+rDUEdKu4iZ0Ouh0C1z3Ctz3E1y+ZJtfqL5StL+MUNQtep3CsfPZqCqM6xXB6G5hWock6gs32BFKwuIE2Xe4kcZtICQGDv9c+bp1lE5RSg0qJkR5rFaVmcsP8Pz/9nBvv5bMGNMFvYzbIlxEcYOMRU4Jibop9QCcPwShXbWOpMYogKp1LzdRJ2SZC3gyfhe/Hkjl+ZEduX9AK+l0K1xO64N2SVgcIjsNt5KfCx8Uzubd9U5tY6lBOkXRfAMh3N/Jizk8MH87p9Mu8+mk3lzToZnWIYn6yA06sUjC4gg5UHEv1nzbfbsboPtEbWOpQToFTl26zNQlicCVn2HxA+eiZtqiZcV/qlcfYTv+vpLvL/6aVVWxqoX31mKPVdspCUvh8oLCxxZLyWVWVaWgcJnFWvJWlqsbCa5+rlMU/j2qEz0jG5b5/vruj1Np3Pv5NgKMXix5tB9RwYFahyTqKzfYD0rCIuqumLGgr78/4T6tGtM1/Bx7TqfbD2yKThHZnxfbzxc9vLqj7tXvLbms5Hvsa5RTrk6noFMUdAqF9wo6ne2xoijoFfDS6dDpiu4VvArf42vQodcpJW+Kgl5vuy9KRkrWqXTMxX29JYmf96Z4bMLy8fpjXM6zsPrpwTSUEW9FDXKDBhZJWIRwVwOimjAgaoDWYbi13afSuJSdp3UYmkjNzGX1/rNM6tdSkhVR89ygT5RcJSSEqJM2HD7PoZQsIhv7aR2KJt5dfQQvncIjg8sex0eI+kYSFgcU5ZVaN4cJIWwOn81k0udb6daiAQ8MbK11OLXu+PlsFmxN4rFr2hLkZ9A6HCFqhSQsQog6Z8OR81isKvPv64OPQa91OLXujZUHaRpoZFK/llqHIkStkYTFEdK0IoRbCQ3yAeBSjuf1X/njVBo//JHMU8PaeWSyJjyXJCyOUK66F25CEklPpSvsAFje5dD12awVB4hqFsCYHjLsvvAskrCIOkgyR0+39dhFGvoZCClsaanIH6fSuOM/Gxn34SbMBZZaiK7mrD98jt+PXOCfI9rjpZfNt/AsclmzEKJOUVWVlfvOcn3nUAxl7LRz8y1sPnqBAymZbDl6gbWHztnP6vZ6ZRV39o7g8Wui6lxn1aK5gnpGNmR4dLDW4QhR6yRhEULUKccv5JB0MYdpZey0s80F/PXLHWw4ch6A7i0a8O+bormzTws2HD7P/y1O5OP1xzh58TKzbovh5KUcOocF1XYVquT7P86w90wGCx+Ok3mChEeShMUZnne6XAi3cyA5A4DQBrbTQWk5eWz68wLrj5znmy1J+Hnree/u7nSLaEB4wytjtAyLDmZbx2a8ufIQ7605woq9KQAE+njxt2vb8tAg9x3PJK/AypsrDzGsYzN6t2ykdThCaEISFodIpiKEu9h1Mg29TqFds0AuZucx+PU1ZOYW2F+fc2d3hpVzykRRFP4xoj3dIhqw/cQlss0FfLn5BD/+kezWCcvCHSc5dSmHjyf20joUITQjCYtTpBlWCK1tOXoBi1Ul01zAgq1JmAusLJ88kI6hJrLMBQQYK9+sDYsOZlh0MJ9tOAbAE0Ojajrsatl7JoOOoSbah8jkhsJzSTdzh1w1MZwQQjPXdQoBbJf3vv3LIW7rEU7HUBOAQ8lKkWW7z/DSD/ucfp8WcvMt+HnLmCvCs0nC4ojCTEXRSQuLW5EB/TzShLhIokNNLN55ir8MaMW0mztVqZzcfNslzn1aNSImvIELI3StzNx8DqZk4uvt3kmVEDVN/gIcYC0cnEpRJL9zC3KFhEcz+Rj44W8DKLCqeHtV/W9ybK8IGvt7c//87Tz81Q7m/6WPC6N0jWPns3nwi+2cTc/luZEdtQ5HCE3JHtgBqtV2r9PLjlIId6DTKdVKVooM7RjMXX1asO7QOY6fz3ZBZK6z7tA5Rr+3Aauq8r/H+9OvTROtQxJCU079xc+dO5eYmBhMJhMmk4m4uDiWL19uf11RlDJvr7/+erllzps3r8z35ObmVr1WLqbaW1g0DkQI4XKDomyJwN4zGRpHcsVHv/3JfZ9vpWdkQ/73WH/aNA3QOiQhNOfUKaHw8HBmzpxJ27ZtAZg/fz6jR49m165ddOrUieTk5BLrL1++nPvvv5/bbrutwnJNJhMHDx4ssczHp/Iht2uLqqqAgqKTBikh6ptrOzbDx6DjYEoGI2NCtQ6H7ccv8upPB/jr4NY8M6IDeuk7JwTgZMIyatSoEs+nT5/O3Llz2bx5M506dSIkJKTE60uXLuWaa66hdevWFZarKEqp97oT1WIBdChedWsobyFE5YxeenpGNmRnUprWoQC2q5eaBhp5dkQHdJKsCGFX5U63FouFhQsXkp2dTVxcXKnXz549y48//sj8+fMrLSsrK4vIyEgsFgvdunXj5Zdfpnv37hW+x2w2Yzab7c8zMmquOddqsXVi0UnCIkS9ZLGqBPlqcw3Cxew81h1KRaco7E/O5ItNJ/jHde0kWRHiKk7/hSYmJhIXF0dubi4BAQEsWbKE6OjoUuvNnz+fwMBAxowZU2F5HTp0YN68eXTp0oWMjAzeeecd+vfvz+7du4mKKn8wpxkzZjBt2jRnw68S1Wq7/FHRyzgIQtRHx85n079t7XdqVVWVR7/eweajFwFbP7nJQ6N47Jq2tR6LEBVxh/TZ6YSlffv2JCQkkJaWxqJFi5g0aRLr1q0rlbR89tlnjB8/vtK+KLGxscTGxtqf9+/fnx49evDuu+8yZ86cct83ZcoUnn76afvzjIwMIiIinK2OQ9TCFhbF4F0j5QshtHMkNYuzGWYUDTbJqgqbj15kQNsmfDihJ3qdgo9BDoyEKIvTCYu3t7e9022vXr3Ytm0b77zzDh9++KF9nfXr13Pw4EG+/fZbpwPS6XT07t2bw4cPV7ie0WjEaDQ6XX5V2PqwgKKXU0JC1DeRjf1o7O+NosDlPAu+tTii7OHULADG922Bv5uPtiuE1qp92YuqqiX6kgB8+umn9OzZk65du1apvISEBEJDte+tb1c0EIteNihC1DcGvY6WTfz5bscp7vl0S61+dvrlfACiguWyZeH+VI1HF3cqYZk6dSrr16/n+PHjJCYm8txzz7F27VrGjx9vXycjI4OFCxfywAMPlFnGxIkTmTJliv35tGnT+Pnnnzl69CgJCQncf//9JCQk8PDDD1exSjXAapsJVi5rFqJ+eu32GMb3bcGOE5dIOJlWK5+Zb7Hy/e4zAJzPyquVzxSiOhSNByNzqsng7NmzTJgwgeTkZIKCgoiJiWHFihUMHz7cvk58fDyqqnLXXXeVWUZSUhK6Yjv+tLQ0HnroIVJSUggKCqJ79+789ttv9OnjPsNkq1ar1iGIsqTuhz/XFD4pzPxVtdjjYsvB1qNR0YGit93rCu/tywpf928KQWG1Vw+huTZNA3hpdGcW7TzFs9/9wc9PDarRz9tzOp2nvk3gcGoWrZr406KRX41+nhD1gaJq3cbjIhkZGQQFBZGeno7JZHJp2fu/+JpfN4byyAfXyKWG7qAgD2a1hPwaGkpd7w1TToFX7fSREu7j2jfWYlFVVkweVGN9Wf48l8VtczcC8NLoztzctXmNfI4QrrRx0RGO/XGe8dNiK1/ZSY7uv6VThiPOHQDcqE+Np/Pyhqf2gLlo7B2l2LwJRY8Ln9sfq7a+SEU3q8XWGqNaSi478gusfgks+TWXsFitttOMJ7fAxjm2BKlZNFz7XM18nnDIpew8whr6sv7weZbvSWZMj3CH35ubb8HopSvRZJ5vsXIwJZPL+RaWJ6ZwOd/Cgq1JAOgU2PnCcBr4yZWHQjhKEhYHqJkpgHtchy4K+TWy3VztQuHVafF3gc7rSlJjtRbeW0rfWy22BMRaUJj4FBRbVrRewZXnXNWo2SwaDq2QhEVDufkWJn2+lf3JGfRu2dDhiQYPpGQwd+2f/Lw3hUZ+3vRr24R2wQH8fuQCe8+kl+ib0sDPQJum/lzfOYRekY0kWRHCSZKwOKLlAEhBMhZPENEXutwBlmKdIBV9YX8X/ZV+Lzq9LaFRCu91+oqX6bwK3+dVclmTKDi9E5Y/o12dBVuOXeSPU+l8MrEXw6KDK1y3wGJl2/FLpOXk8eyiP1CB9iEm2jT1Z2fSJb7bcYomAd6M7hZGm6YBBPkaiG3diMYBcopRiOqQhEWI4oLC4bZPavczT++s3c8TpZjzbWMtdQkPqnTd134+yEe/HQUgtnUjPprYC5PPlTGazmeZaejnLZMWCuFikrA4orAFX+tLuoQQNSOtcDyUgAoGbyuwWPnHwt38L+EM9/VvyZ29W9AuOKDUdqGJtKSIesgdrs6RhEUI4fGaFiYZqZlmWpWRtKiqyv8SzvC/hDMM6xjMCyOj5YpBIWqZJCwOcIfMUghRc6yFoztkmwtKvZaSnssbKw/y3Y5TGPQK00Z3kmRFCA1IwuIwGTxOiPqqrDFX8i1WNh+9wCNf7USnwPMjO3JnnxYVnjYSQtQc+csTQng8b71t9G2DXofFqqLXKTz85Q5WH0ilU3MT3zwQS5CfTH4qhJYkYXGAqsoVzULUZ0WXHN/7+VaS03MJMfmQkpHLvf1a8sJN0XLFjxBuQBIWh0lPFiHqqwKL7ZRvcnouvgY9PSMbckv3MIZ1bCZXBwrhJiRhcYhssISoz6KCA/n+8QF0DA3ESy+zsgvhjiRhcZAiLSxC1GuODBonhNCOHEoIIYQQomKq9gftkrA4wA2+JyGEEEJTWnfnkoTFYZK1iBqi97bN5LzpAygwax2NEEK4JUlYhNBa5zHQYxKsfA7e6wV//BesMlChEEIUJwmLA1S0bwoT9Zi3P9w8Bx7dDCExsPhB+GgQ/Pmr1pEJIYTbkITFYXJKSNSwpu3hzq/hLyvB4A9fjoELf2odlRBCuAVJWByhSvOKqEUt+sLY+YAK5w9pHY0QQrgFSVgcoCLjsIha5t8MdAZIP6V1JEII4RYkYRHCHel0YGouCYsQwi24wyG7JCxCuKugcElYhBCikCQsjlDt/xOi9kT0hYM/QVqS1pEIIYTmJGERwl0NfBp8GsDy/9M6EiGE0JwkLA6wdboVopYZA+H6GXDwRzi4XOtohBBCU5KwOELOBgmtRI+GtsPgp2cgL1vraIQQQjOSsDhMshahAUWBG1+H7FT47XWtoxFCCM1IwuIAFUXGYRHaadQaBv4dNr4Lqfu1jkYI4YncYBcoCYsQdUH/ydCwJfz4d1DdYMshhBC1TBIWR0mvW6ElLyOMfBNO/A67F2gdjRBC1DqnEpa5c+cSExODyWTCZDIRFxfH8uVXrl5QFKXM2+uvV3zufdGiRURHR2M0GomOjmbJkiVVq00NUVUZml+4gdZDoPPtsPJ5yLmodTRCCFGrnEpYwsPDmTlzJtu3b2f79u1ce+21jB49mr179wKQnJxc4vbZZ5+hKAq33XZbuWVu2rSJcePGMWHCBHbv3s2ECRMYO3YsW7ZsqV7NhKiPRrwKlgJYPU3rSIQQolYpqlq9E+KNGjXi9ddf5/777y/12i233EJmZiarV68u9/3jxo0jIyOjREvN9ddfT8OGDVmwwPGm74yMDIKCgkhPT8dkMjlXiUrs/PArdu428cAHN7u0XCGqZOvH8NM/4OHfIaSz1tEIITzAhoWHSdp7gbtfjHV52Y7uv72q+gEWi4WFCxeSnZ1NXFxcqdfPnj3Ljz/+yPz58yssZ9OmTTz11FMllo0YMYLZs2dX+D6z2YzZbLY/z8jIcDz4Ksiz+vLd378stbw66Z6qOt4xpuyPKf/9lcdVtU45FRZbSX2q/k9VnXqWT61Gx6SKvjtfbzM9rmmC3mgAtXiMatF/9n8M+/GCWuwxV95T/HX7cmsoat4wWLQUejUBVb2qTNuTEv82xcovuVwt9llXVlZVSnxh1TyuKZNTRdbyGVlFB3ovHXqDDr2XDi+D7bGXt74wnmL/5iqoV323Jb7XovWvXres38BVr4HtynYUUGz/K7ZcKfW6iopqtZWpqrbHRZ+tFt1br7pXVXvMV79XVUuuY7Xagrv6tVLlWa/8+1RY/2L/jiV+t2X8Xq/EeaXgos++sl5hna/+d726vGKPSy6vZL3C+ui9dPiZDLbXrGC1FP2bqVitV2JAKfx+Cr8vL4MOb18vvH30hfdeGHz0KDqlxHrFv+8SyyldLhR7r+7Kb+LKY9vrtt9J0eOisgvX0V31eUrJeBQFMi/mojWnE5bExETi4uLIzc0lICCAJUuWEB0dXWq9+fPnExgYyJgxYyosLyUlheDg4BLLgoODSUlJqfB9M2bMYNq02mkWbzWwO+kXtji/0Sxnn1bhbtLZ91RQWFU+x5EVlErfW0GpVX1vVetZ6XurVnBFn3n0uA/LfzBWFlU1eAOPwUUgcZ9zby3a5xVtqIr+pxT7t1CKLy/2L+Tgd+fUV+zED6I6vztHqartc6xWFUuBFWtBPey7phTfiRXumHQKuqKd3NWv64o/xr4z0+mUEjtARVesvBI7vCs7SNvzKzvJEjvbEusVlXPl96ortgO+ssMuvd7VCZ49Hspa76rluuLPy3m/AgV5Vi5n5tnjUnS2fztFV/i8qFIlEjKVgnwreZcLyMnMIy31MnmXC8gzW0oklSUOPIonZPaFXEkE7Y/VK8lzsfe4WmjboJop2EFOJyzt27cnISGBtLQ0Fi1axKRJk1i3bl2ppOWzzz5j/Pjx+Pj4VFpmicwR2z/41cuuNmXKFJ5++mn784yMDCIiIpyoieMaRnfimuhONVK2qH/65OaSczYZKL5xLL5VLra8aCX7Y9vWtmgjaV9UtPFEgaINt7c/ePuUPPIuq2xK/40Jx6iFiUtBvhVLvpWCfEvhK1d2tCWOVK/aidqWld6J2tct63sqnjA60mpjX6aWSDQoTCoURYFiyYT8FjxDiZYzAKvtN1LUGmZbp/jjKy1Y9lYmKxS1eqmqim+gtyZ1KeJ0wuLt7U3btm0B6NWrF9u2beOdd97hww8/tK+zfv16Dh48yLfffltpeSEhIaVaU1JTU0u1ulzNaDRiNNbkUawQVaP38SEwspXWYQgXUHQKXt76K6eChKgjSpxaAqgHP+Fqj8OiqmqJviQAn376KT179qRr166Vvj8uLo5ffvmlxLKVK1fSr1+/6oYmhBBCiHrCqRaWqVOncsMNNxAREUFmZibx8fGsXbuWFStW2NfJyMhg4cKFvPnmm2WWMXHiRMLCwpgxYwYAkydPZtCgQcyaNYvRo0ezdOlSVq1axYYNG6pRLSGEEELUJ04lLGfPnmXChAkkJycTFBRETEwMK1asYPjw4fZ14uPjUVWVu+66q8wykpKS0OmuNOz069eP+Ph4nn/+eV544QXatGnDt99+S9++fatYJSGEEELUN9Ueh8Vd1OQ4LEIIIYSoGY7uv2UuISGEEEK4PUlYhBBCCOH2JGERQgghhNuThEUIIYQQbk8SFiGEEEK4PUlYhBBCCOH2JGERQgghhNuThEUIIYQQbk8SFiGEEEK4Padna3ZXRQP2ZmRkaByJEEIIIRxVtN+ubOD9epOwZGZmAhAREaFxJEIIIYRwVmZmJkFBQeW+Xm/mErJarZw5c4bAwEAURamxz8nIyCAiIoKTJ0965JxFnl5/kH8Dqb/U35PrD/Jv4Or6q6pKZmYmzZs3LzE58tXqTQuLTqcjPDy81j7PZDJ55A+1iKfXH+TfQOov9ffk+oP8G7iy/hW1rBSRTrdCCCGEcHuSsAghhBDC7UnC4iSj0ci///1vjEaj1qFowtPrD/JvIPWX+nty/UH+DbSqf73pdCuEEEKI+ktaWIQQQgjh9iRhEUIIIYTbk4RFCCGEEG5PEhYhhBBCuD1JWCowffp0+vXrh5+fHw0aNChznaSkJEaNGoW/vz9NmjThiSeeIC8vr8Q6//3vf+nWrRt+fn5ERkby+uuv10L01eeq+v/888/ExsYSGBhI06ZNue222zh27Fgt1KB6XFH/F198EUVRSt38/f1rqRZV56rvX1VV3njjDdq1a4fRaCQiIoJXX321FmpQPa6o//Hjx8v8/lesWFFLtageV/0Gihw5coTAwMByy3I3rqj/wYMHueaaawgODsbHx4fWrVvz/PPPk5+fX0u1qDpX1H/t2rWMHj2a0NBQ/P396datG19//XWV4qk3I93WhLy8PO644w7i4uL49NNPS71usVgYOXIkTZs2ZcOGDVy4cIFJkyahqirvvvsuAMuXL2f8+PG8++67XHfddezfv58HHngAX19fHn/88dquklNcUf+jR48yevRonn76ab7++mvS09N56qmnGDNmDLt27artKjnFFfX/xz/+wcMPP1zifUOHDqV37961UofqcEX9ASZPnszKlSt544036NKlC+np6Zw/f742q1Ilrqo/wKpVq+jUqZP9eaNGjWo8fldw5b9Bfn4+d911FwMHDmTjxo21VYVqcUX9DQYDEydOpEePHjRo0IDdu3fz4IMPYrVa3T5xd0X9N27cSExMDM8++yzBwcH8+OOPTJw4EZPJxKhRo5wLSBWV+vzzz9WgoKBSy3/66SdVp9Opp0+fti9bsGCBajQa1fT0dFVVVfWuu+5Sb7/99hLve/vtt9Xw8HDVarXWaNyuUp36L1y4UPXy8lItFot9nWXLlqmKoqh5eXk1HrsrVKf+V0tISFAB9bfffqupcF2uOvXft2+f6uXlpR44cKC2wnW56tT/2LFjKqDu2rWrlqKtGa74G3jmmWfUe+65p9yy3JkrtwGqqqpPPfWUOmDAgJoItUa4uv433nijet999zkdh5wSqoZNmzbRuXNnmjdvbl82YsQIzGYzO3bsAMBsNuPj41Pifb6+vpw6dYoTJ07Uaryu5kj9e/XqhV6v5/PPP8disZCens6XX37Jddddh8Fg0Cp0l3Ck/lf75JNPaNeuHQMHDqytMGuMI/X//vvvad26NT/88AOtWrWiZcuWPPDAA1y8eFGrsF3Gme//5ptvplmzZvTv35/vvvuutkOtMY7+G/z6668sXLiQ999/X4swa0xVtgFHjhxhxYoVDB48uLbCrDFVqT9Aenp6lVoZJWGphpSUFIKDg0ssa9iwId7e3qSkpAC2L2/x4sWsXr0aq9XKoUOHmD17NgDJycm1HbJLOVL/li1bsnLlSqZOnYrRaKRBgwacOnWK+Ph4LUJ2KUfqX5zZbObrr7/m/vvvr60Qa5Qj9T969CgnTpxg4cKFfPHFF8ybN48dO3Zw++23axGySzlS/4CAAN566y2+++47fvrpJ4YOHcq4ceP46quvtAjZ5Rz5N7hw4QL33nsv8+bNq3cTBTqzDejXrx8+Pj5ERUUxcOBAXnrppdoMtUY4uw0E+O6779i2bRv33Xef05/ncQlLeZ0gi9+2b9/ucHmKopRapqqqffmDDz7I448/zk033YS3tzexsbHceeedAOj1etdUygm1Xf+UlBQeeOABJk2axLZt21i3bh3e3t7cfvvtqBoMslzb9S9u8eLFZGZmMnHixGrVoTpqu/5WqxWz2cwXX3zBwIEDGTJkCJ9++ilr1qzh4MGDLquXo2q7/k2aNOGpp56iT58+9OrVi5deeolHH32U1157zWV1cpYW28C7776bQYMGuawO1aHVNuDbb79l586dfPPNN/z444+88cYb1a5LVWi5DVy7di333nsvH3/8cYk+XY7yuE63jz/+uD1hKE/Lli0dKiskJIQtW7aUWHbp0iXy8/PtWaeiKMyaNYtXX32VlJQUmjZtyurVq536HFeq7fq///77mEymEhvor776ioiICLZs2UJsbKxzFaim2q5/cZ988gk33XQTISEhDsfrarVd/9DQULy8vGjXrp19nY4dOwK2qwvat2/vRPTVp+X3XyQ2NpZPPvnEoc+oCbX9b/Drr7+ybNky+w5aVVWsViteXl589NFH/OUvf3G+EtWg1W8gIiICgOjoaCwWCw899BB///vfa/3AVav6r1u3jlGjRvHWW29V+aDN4xKWJk2a0KRJE5eUFRcXx/Tp00lOTiY0NBSAlStXYjQa6dmzZ4l19Xo9YWFhACxYsIC4uDiaNWvmkjicUdv1z8nJKfUHWfTcarW6JA5naPX9Hzt2jDVr1rBs2TKXfHZV1Xb9+/fvT0FBAX/++Sdt2rQB4NChQwBERka6JA5naPX9F7dr1y77+lqo7X+DTZs2YbFY7O9ZunQps2bNYuPGjfZtYm1yh9+Aqqrk5+dr0sqsRf3Xrl3LTTfdxKxZs3jooYeq/oFOd9P1ICdOnFB37dqlTps2TQ0ICFB37dql7tq1S83MzFRVVVULCgrUzp07q0OHDlV37typrlq1Sg0PD1cff/xxexnnzp1T586dq+7fv1/dtWuX+sQTT6g+Pj7qli1btKqWw1xR/9WrV6uKoqjTpk1TDx06pO7YsUMdMWKEGhkZqebk5GhVNYe4ov5Fnn/+ebV58+ZqQUFBbVejylxRf4vFovbo0UMdNGiQunPnTnX79u1q37591eHDh2tVLYe5ov7z5s1Tv/76a3Xfvn3qgQMH1Ndff101GAzqW2+9pVW1nOLKv4EidekqIVfU/6uvvlK//fZbdd++feqff/6p/ve//1XDwsLU8ePHa1Uth7mi/mvWrFH9/PzUKVOmqMnJyfbbhQsXnI5HEpYKTJo0SQVK3dasWWNf58SJE+rIkSNVX19ftVGjRurjjz+u5ubm2l8/d+6cGhsbq/r7+6t+fn7q0KFD1c2bN2tQG+e5ov6qarvMrXv37qq/v7/atGlT9eabb1b3799fy7Vxnqvqb7FY1PDwcHXq1Km1XIPqcVX9T58+rY4ZM0YNCAhQg4OD1XvvvbdKG6va5or6z5s3T+3YsaPq5+enBgYGqj179lS//PJLDWpTNa76DRRXlxIWV9Q/Pj5e7dGjhxoQEKD6+/ur0dHR6quvvqpevnxZgxo5xxX1L6+MwYMHOx2PoqoatEkJIYQQQjjB464SEkIIIUTdIwmLEEIIIdyeJCxCCCGEcHuSsAghhBDC7UnCIoQQQgi3JwmLEEIIIdyeJCxCCCGEcHuSsAghhBDC7UnCIoQQQgi3JwmLEEIIIdyeJCxCCCGEcHuSsAghhBDC7f0/hYItACN6DakAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for t in swapCandidates:\n",
    "    geo = unitGeom[HDunitList[t][0]]\n",
    "    for u in HDunitList[t]:\n",
    "        geo = geo.union(unitGeom[u])\n",
    "    plotPoly(geo)\n",
    "    plotPoly(unitGeom[UUU])\n",
    "    plotPoly(hdCP[t].buffer(0.2))\n",
    "    plotPoly(countyGeom[16])\n",
    "    plotPoly(MAP)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "0a9a97cb-b4f5-43d4-868d-8dd7aecf684e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):  #this is before the Denver triage below\n",
    "    if unitUse[u] > 1.15:\n",
    "        plotPoly(unitGeom[u])\n",
    "    if unitUse[u] < 0.95:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "d12e1ca9-c09c-4c72-81ee-580cfb05ef36",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after below Denver triage\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"after below Denver triage\")\n",
    "for u in range(nUnits):  \n",
    "    if unitUse[u] > 1.15:\n",
    "        plotPoly(unitGeom[u])\n",
    "    if unitUse[u] < 0.95:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "7efa9801-1e93-444d-b1e2-cb5f1f54db95",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "looking for E HDs that could trade out Denver\n",
      "there are 511 eastern HDs with potential to trade out an avg of 120755.63992 overused Denver pop\n"
     ]
    }
   ],
   "source": [
    "print(\"looking for E HDs that could trade out Denver\")\n",
    "Etradeouts, EswapPops = list(),list()\n",
    "for t in range(nHDs):\n",
    "    if hdCP[t].x > -105 :\n",
    "        OUset = set(OUUcontig).intersection(set(HDunitList[t]) )\n",
    "        if len(OUset) > 5:\n",
    "            Etradeouts.append(t)\n",
    "            EswapPops.append(np.sum([unitPop[u] for u in OUset]) )\n",
    "print(\"there are\",len(Etradeouts),\"eastern HDs with potential to trade out an avg of\",r5(np.average(EswapPops)),\"overused Denver pop\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "2924c9e0-8003-48ee-be4b-7444dedab49a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "DenverDist = [hdCP[t].distance(countyCP[16]) for t in Etradeouts]\n",
    "idx = np.argsort(DenverDist)\n",
    "farthestFirst = list()\n",
    "for i, t in enumerate(Etradeouts):\n",
    "    farthestFirst.append(Etradeouts[idx[int(-i-1)]])\n",
    "#plotPoly(MAP)\n",
    "plotPoly(countyGeom[16])\n",
    "for i,t in enumerate(farthestFirst):\n",
    "    plotCenter(i,hdCP[t],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "0a163a28-537e-4749-81b7-6fe041a49edf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 72171\n",
      "current avg and SD of unit usage are 0.99963 0.09004 . Now trying to reduce up to 255 units' overusage\n",
      "10 patches tried.  Current avg and SD of usage are 0.99962 0.08907\n",
      "20 patches tried.  Current avg and SD of usage are 0.99962 0.08819\n",
      "30 patches tried.  Current avg and SD of usage are 0.99962 0.08728\n",
      "40 patches tried.  Current avg and SD of usage are 0.99962 0.08634\n",
      "50 patches tried.  Current avg and SD of usage are 0.99963 0.0856\n",
      "60 patches tried.  Current avg and SD of usage are 0.99962 0.08489\n",
      "70 patches tried.  Current avg and SD of usage are 0.99962 0.08429\n",
      "80 patches tried.  Current avg and SD of usage are 0.99962 0.08361\n",
      "90 patches tried.  Current avg and SD of usage are 0.99962 0.08294\n",
      "100 patches tried.  Current avg and SD of usage are 0.99963 0.0824\n",
      "110 patches tried.  Current avg and SD of usage are 0.99963 0.08188\n",
      "120 patches tried.  Current avg and SD of usage are 0.99963 0.08126\n",
      "130 patches tried.  Current avg and SD of usage are 0.99963 0.08074\n",
      "140 patches tried.  Current avg and SD of usage are 0.99963 0.07998\n",
      "150 patches tried.  Current avg and SD of usage are 0.99963 0.07955\n",
      "160 patches tried.  Current avg and SD of usage are 0.99963 0.07906\n",
      "170 patches tried.  Current avg and SD of usage are 0.99963 0.07848\n",
      "180 patches tried.  Current avg and SD of usage are 0.99963 0.07794\n",
      "190 patches tried.  Current avg and SD of usage are 0.99963 0.07725\n",
      "200 patches tried.  Current avg and SD of usage are 0.99963 0.07675\n",
      "210 patches tried.  Current avg and SD of usage are 0.99963 0.07647\n",
      "220 patches tried.  Current avg and SD of usage are 0.99963 0.07617\n",
      "230 patches tried.  Current avg and SD of usage are 0.99963 0.07571\n",
      "240 patches tried.  Current avg and SD of usage are 0.99963 0.07531\n",
      "250 patches tried.  Current avg and SD of usage are 0.99963 0.07497\n",
      "all done trying to selectively patch down urban area 391 sec elapsed 235 20 successful, failed patches, couldn't start= 0\n"
     ]
    }
   ],
   "source": [
    "#2/16/24 modified PATCHING BLOCK -- OVERUSERS, drawing only from above list  #\n",
    "maxSD = 0.05\n",
    "maxExchangePop = 0.1*aDP \n",
    "minOverUse = 1.01\n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = int(0.5*len(farthestFirst))  #SPECIAL FOR this list\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "nTries,nPatchSuccess,nCouldntStart,nPatchFail = 0,0,0,0\n",
    "while currSD > maxSD and nTries < maxNtries: \n",
    "    t = farthestFirst[nTries]\n",
    "    nTries +=1\n",
    "    #simpler than usual -- just try to jettison a contiguous OUU cluster from all pre-ID'd HDs\n",
    "    reallyOUlist = list(set(OUUcontig).intersection(set(HDunitList[t]) ) )\n",
    "    OUlist = list()\n",
    "    for u in HDunitList[t]:\n",
    "        if unitUse[u] > minOverUse:\n",
    "            OUlist.append(u)\n",
    "    OUlist = getContigFromStarter(reallyOUlist[0],OUlist,unitNbrs)  #all overused units in this HD contiguous with the super-overused cluster\n",
    "    if len(OUlist) > 0:\n",
    "        bdryCandidates = getBdryNonEdgers(HDunitList[t], unitNbrs)\n",
    "        OUbdryCandidates = list(set(bdryCandidates).intersection(set(OUlist)) )\n",
    "        notGiveUpOnShedding,shedPop = True,0\n",
    "        if len(OUbdryCandidates) > 0: #at least one of the contiguous OUU's adjoins the complement\n",
    "            OUbdryScore = [unitUse[u] for u in OUbdryCandidates]\n",
    "            shedStarter = OUbdryCandidates[OUbdryScore.index(np.max(OUbdryScore)) ]\n",
    "            shedSet, shedPop = {shedStarter}, unitPop[shedStarter]\n",
    "            trySet = set(HDunitList[t]).difference(shedSet)\n",
    "            giveUpOnShedding = False\n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if shedPop + unitPop[u] <= maxExchangePop and unitUse[u] > minOverUse:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            while shedPop < maxExchangePop and not giveUpOnShedding:   \n",
    "                if len(shedCandidates) == 0:\n",
    "                    giveUpOnShedding = True\n",
    "                while shedPop < maxExchangePop and not giveUpOnShedding:\n",
    "                    idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                    while ij < len(shedScores) and notYetPicked:\n",
    "                        listNo = idx[-1-ij]   #work from high to low score\n",
    "                        shedU = shedCandidates[listNo]\n",
    "                        if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                            break\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            shedPop += unitPop[shedU]\n",
    "                            #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                            shedSet.add(shedU)\n",
    "                            trySet.remove(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if shedPop + unitPop[u] <= maxExchangePop and u not in shedCandidates and unitUse[u] > minOverUse:\n",
    "                                    shedCandidates.append(u)\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                        else:\n",
    "                            ij +=1\n",
    "                    if notYetPicked:\n",
    "                        giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "                #shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "                trySet = set(HDunitList[t]).difference(shedSet) \n",
    "                gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "                nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "                for u in trySet:\n",
    "                    for uu in unitNbrs[u]:\n",
    "                        if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < minOverUse:\n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                            #bias toward UNDERUSED, close\n",
    "                addedSet = set( )    \n",
    "                stillGoing = True\n",
    "                while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                    idx, ij, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "                    while ij < len(nearHDscore) and notYetPicked:        \n",
    "                        listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                        unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                        canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                        if canAdd:\n",
    "                            notYetPicked = False\n",
    "                        else:\n",
    "                            ij +=1\n",
    "                    if notYetPicked:\n",
    "                        stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                    else:\n",
    "                        gap -= unitPop[unitNoToAdd]\n",
    "                        addedSet.add(unitNoToAdd)\n",
    "                        trySet.add( unitNoToAdd)\n",
    "                        for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                            if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < minOverUse:  \n",
    "                                nearHDlist.append(uu)\n",
    "                                nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                                #bias toward UNDERUSED, ~close\n",
    "                        del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                        del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                        for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                            if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                                del nearHDscore[nearHDlist.index(uu)]\n",
    "                                del nearHDlist[ nearHDlist.index(uu)]\n",
    "                tryPop = np.sum([unitPop[u] for u in trySet])\n",
    "\n",
    "                legitSwap = False\n",
    "                if abs(gap) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                    if contig and cContig:\n",
    "                        legitSwap = True\n",
    "                if legitSwap:\n",
    "                    for u in shedSet:\n",
    "                        unitUse[u] -= HDweight[t] * nDistricts\n",
    "                    for u in addedSet:\n",
    "                        unitUse[u] += HDweight[t] * nDistricts\n",
    "                    HDunitList[t] = list(trySet)\n",
    "                    HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                    nPatchSuccess +=1\n",
    "                    #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "                else:\n",
    "                    nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "            \n",
    "\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    if nTries%10 == 0:\n",
    "        print(nTries,\"patches tried.  Current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n",
    "print(\"all done trying to selectively patch down urban area\",int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "0c7c79a3-8cd8-44c9-85ba-6257d490a5cb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 0.99963 0.99959 and their SDs are 0.09004 0.05965\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 3108\n",
      "working on HD 300 out of 3108\n",
      "working on HD 600 out of 3108\n",
      "working on HD 900 out of 3108\n",
      "working on HD 1200 out of 3108\n",
      "working on HD 1500 out of 3108\n",
      "working on HD 1800 out of 3108\n",
      "working on HD 2100 out of 3108\n",
      "working on HD 2400 out of 3108\n",
      "working on HD 2700 out of 3108\n",
      "working on HD 3000 out of 3108\n",
      "all done checking HD and complement contiguity for all 3108 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "812afac6-9c0b-4018-b059-268aea9b38f2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing vtdlist for comparing ensemble district margin to actual\n",
      "Must have already established unitGeoms, pops, topology\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched vtdlist, e.g. ./2024state_HD_output/CO3108contigUnpatchedB.csv ./2024state_HD_output/CO3108contigPatchUpBetter.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I read in 3108 HD lists of vtds\n"
     ]
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing vtdlist for comparing ensemble district margin to actual\")\n",
    "print(\"Must have already established unitGeoms, pops, topology\")\n",
    "infile = input(\"enter the unpatched vtdlist, e.g. ./2024state_HD_output/CO3108contigUnpatchedB.csv\")\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of vtds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "3ad3342b-b8e3-46f5-a3e5-f49df386b88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\n",
      "Let's read in the 2020 and 2016 voting data for CO\n",
      "In year/election 2020 Dem and GOP total votes were 1804347 1364598 for a stateGOP of 0.43062\n",
      "There are a total of 3108  vote-mapped voting districts from election(s) in year  2020\n",
      "In year/election 2016 Dem and GOP total votes were 1338867 1202477 for a stateGOP of 0.47317\n",
      "There are a total of 3108  vote-mapped voting districts from election(s) in year  2016\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\")\n",
    "#note: we started w possibility of separate election --> 2020 vtd files by year.  Now we use ALARM combined 2016+2020 --> 2020 csv's for all exc CA\n",
    "# copied from \"HDpartisanAnalysis\"\n",
    "print(\"Let's read in the 2020 and 2016 voting data for\",STATE)\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G16PREDCLI\"], [\"G16PRERTRU\" ], list()\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G20PREDBID\", \"G16PREDCli\"], [\"G20PRERTRU\" ,\"G16PRERTru\" ], list()\n",
    "DemCandidates, RepCandidates, vestDFs = [\"pre_20_dem_bid\", \"pre_16_dem_cli\"], [\"pre_20_rep_tru\" ,\"pre_16_rep_tru\" ], list()\n",
    "nYears = 2\n",
    "unitIDs, vestReps,vestDems,yearLean = [list()]*nYears, [0]*nYears, [0]*nYears, [0.5]*nYears\n",
    "years = [str(2020),str(2016)]\n",
    "DemVotes, RepVotes = [list() for y in years], [list() for y in years]\n",
    "vestDir = \"./state_map_files/\" + STATE.lower()\n",
    "vestDF = pd.read_csv(vestDir + \"_2020_vtd.csv\")\n",
    "vestDF['GEOID20'] = vestDF['GEOID20'].astype(str)\n",
    "mergedDF = vestDF.copy() #pd.merge(mergedDF,vestDF, on = \"GEOID20\")\n",
    "for y,year in enumerate(years):\n",
    "    DemVotes[y], RepVotes[y], unitIDs[y] = mergedDF[DemCandidates[y]], mergedDF[RepCandidates[y]], vestDF[(\"GEOID20\")]\n",
    "    vestDems[y], vestReps[y] = np.sum(DemVotes[y]), np.sum(RepVotes[y])\n",
    "    yearLean[y] = vestReps[y]/float(vestDems[y]+vestReps[y])\n",
    "    print(\"In year/election\",year,\"Dem and GOP total votes were\",int(vestDems[y]),int(vestReps[y]),\"for a stateGOP of\",r5(yearLean[y]) )\n",
    "    nVTDs = len(DemVotes[y])\n",
    "    print(\"There are a total of\",nVTDs,\" vote-mapped voting districts from election(s) in year \",years[y])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "5cf73783-4a48-4a3f-a2e3-c1b9ff32c859",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's read in our ensemble of HD districts for CO\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the filename with the vtd assignments to districts; e.g. CO3108contigPatchUpBetter.csv CO3108contigPatchEvenMore.csv\n",
      "enter the number of districts in the state; e.g. 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This ensemble or enacted map describes 3108 drawn districts.  This state has 8 districts per map\n",
      "converting vtd list strings to vtd lists by drawn district ...\n",
      "the total weight across all rows should be 1.000, actually is 1.0\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's read in our ensemble of HD districts for\",STATE)\n",
    "infilename = input(\"enter the filename with the vtd assignments to districts; e.g. CO3108contigPatchUpBetter.csv\")\n",
    "#infilename = \"GA_nD14tol0.01nW4.csv\"  #MO1654contigPatchBoth.csv\n",
    "HDdf = pd.read_csv(\"2024state_HD_output/\"+infilename)\n",
    "nRows = len(HDdf)\n",
    "nStateDistricts = int(input(\"enter the number of districts in the state; e.g. 8\"))\n",
    "print(\"This ensemble or enacted map describes\",nRows,\"drawn districts.  This state has\",nStateDistricts,\"districts per map\")\n",
    "\n",
    "HDvPop = HDdf[\"HDvPop\"].to_list()\n",
    "HDweight = HDdf['HDweight'].to_list()\n",
    "HDwt = HDweight.copy()\n",
    "#tractPop = HDdf['tractPop'].to_list()\n",
    "#statePop = np.sum(tractPop)\n",
    "tractCPx = HDdf['centroid x'].to_list()\n",
    "tractCPy = HDdf['centroid y'].to_list()\n",
    "HDvtdListString = HDdf[\"HDvtdList\"]\n",
    "print(\"converting vtd list strings to vtd lists by drawn district ...\")\n",
    "HDvtdList = [list() for t in range(nRows) ]\n",
    "for t in range(nRows):\n",
    "    if HDvtdListString[t] != \"[]\":\n",
    "        HDvtdList[t] = ast.literal_eval(HDvtdListString[t])\n",
    "\n",
    "if \"splitTractNo\" in HDdf.columns.values: #.to_list():\n",
    "    splitTractNo, splitTractUse = HDdf['splitTractNo'], HDdf['splitTractUse']\n",
    "else :  #incoming file didn't use any partial units, only whole ones\n",
    "    splitTractNo, splitTractUse = [-999 for t in range(nRows)] , [0. for t in range(nRows)]\n",
    "\n",
    "print(\"the total weight across all rows should be 1.000, actually is\",r5(np.sum(HDwt)) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "f3235bcf-de96-4232-805e-149cfc8aae71",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\n",
      "lets make sure the election geoid's are interpreted as strings of the correct length, so we can merge\n",
      "<class 'str'> <class 'str'>\n",
      "08017017002 08001001002\n",
      "translating from HD order of precinct rows to VEST order\n"
     ]
    }
   ],
   "source": [
    "print(\"I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\")\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "geoidNameLength = len(censusGEOID20[0])\n",
    "print(\"lets make sure the election geoid's are interpreted as strings of the correct length, so we can merge\")\n",
    "print(type(tractPopFile['GEOID20'][1]), type(mergedDF['GEOID20'][1]))\n",
    "print((tractPopFile['GEOID20'][1]), (mergedDF['GEOID20'][1]))\n",
    "mDFgeoL = len(mergedDF['GEOID20'][0])\n",
    "if mDFgeoL < geoidNameLength :\n",
    "    mergedDF['GEOID20'].to_list()\n",
    "    print(\"The election file has GEOID20 column of length\",mDFgeoL,\"vs Census VTD file name length\",geoidNameLength)\n",
    "    newGeo = [\"0\"*(geoidNameLength - len(gid)) + gid for gid in mergedDF['GEOID20'] ]\n",
    "    mergedDF['GEOID20'] = newGeo.copy()\n",
    "        \n",
    "miniHDdf = pd.DataFrame( {\"GEOID20\":censusGEOID20} )\n",
    "vestNo = [v for v in range(nVTDs)]\n",
    "print(\"translating from HD order of precinct rows to VEST order\")\n",
    "miniVestDF = pd.DataFrame( {\"GEOID20\":mergedDF['GEOID20'], \"vestNo\":vestNo} )\n",
    "mappingDF = pd.merge(miniHDdf,miniVestDF,on=\"GEOID20\")\n",
    "vestID = mappingDF['vestNo']  #this maps each named unit in a HDVL to the correct vestNo row with voting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "9c38b293-7a46-4106-a972-b4868206bc2d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "vtdGeom = tractPopFile['geometry']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "540c6d1d-7728-48bf-90f0-f124b25ac7c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sanity check - Dem-leaning vtds for year 2020\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = 0\n",
    "print(\"sanity check - Dem-leaning vtds for year\",years[y])\n",
    "vtdLean = [(RepVotes[y][vestID[v]] + 0.001)/(RepVotes[y][vestID[v]] + 0.001 + DemVotes[y][vestID[v]] + 0.001) for v in range(nVTDs) ]\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.2)\n",
    "    if vtdLean[v] < 0.5 :\n",
    "        plt.text(vtdGeom[v].centroid.x, vtdGeom[v].centroid.y, \"d\", color = \"blue\",fontsize=6)\n",
    "        #plotCenter(\"d\",vtdGeom[v],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "56ed7e9d-1400-4848-892e-737555552d58",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\n",
      "working on drawn district no 0\n",
      "working on drawn district no 500\n",
      "working on drawn district no 1000\n",
      "working on drawn district no 1500\n",
      "working on drawn district no 2000\n",
      "working on drawn district no 2500\n",
      "working on drawn district no 3000\n",
      "here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\n",
      "true 2020: 1804347 1364598 -439748\n",
      "ensemble : 1815582 1352557 -463025\n",
      "the true and ensemble state GOP leans are 0.43062 0.4269247036837257\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\")\n",
    "nDrawnDistricts = len(HDwt)\n",
    "nEnsembleDems, nEnsembleReps = [0.]*nYears, [0.]*nYears\n",
    "y=0\n",
    "for t in range(nDrawnDistricts):\n",
    "    if t%500 == 0:\n",
    "        print(\"working on drawn district no\",t)\n",
    "    nEnsembleDems[y] += nStateDistricts* HDwt[t] * np.sum([DemVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "    nEnsembleReps[y] += nStateDistricts* HDwt[t] * np.sum([RepVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "\n",
    "print(\"here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\")\n",
    "print(\"true 2020:\",int(vestDems[y]),int(vestReps[y]),              int(vestReps[y] - vestDems[y]) )\n",
    "print(\"ensemble :\",int(nEnsembleDems[y]),int(nEnsembleReps[y]),    int(nEnsembleReps[y] - nEnsembleDems[y]) )\n",
    "print(\"the true and ensemble state GOP leans are\",r5(vestReps[y]/(vestReps[y]+vestDems[y])),\n",
    "      nEnsembleReps[y]/(nEnsembleReps[y]+nEnsembleDems[y]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5c607c63-df0d-4334-8131-368c090c76d2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "uh oh, we have a bias in usage.  Here's that scatterplot\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"uh oh, we have a bias in usage.  Here's that scatterplot\")\n",
    "vtdUse = [0. for v in range(nVTDs) ]\n",
    "for t in range(nRows):\n",
    "    for v in HDvtdList[t]:\n",
    "        vtdUse[v] += float(nStateDistricts) * HDweight[t]\n",
    "plt.scatter(vtdLean, vtdUse)\n",
    "plt.xlabel(\"vtd pct GOP\")\n",
    "plt.ylabel(\"vtd usage in ensemble\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9c71c2d3-c5a1-449b-bd39-52915eab27aa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "visualizing where we have strong d or GOP lean and overuse\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Dem districts leaning less than 30pct for Trump and use > 1.15 are\n",
      "[290, 292, 299, 301, 302, 306, 307, 308, 309, 310, 311, 317, 318, 319, 327, 328, 329, 340, 344, 346, 355, 357, 385, 387, 388, 389, 390, 391, 392, 393, 398, 399, 400, 407, 408, 415, 416, 419, 420, 422, 424, 425, 427, 428, 429, 430, 436, 440, 446, 453, 459, 460, 461, 467, 472, 473, 478, 480, 484, 486, 487, 488, 494, 495, 503, 504, 509, 510, 513, 514, 515, 519, 521, 522, 527, 528, 531, 572, 583, 584, 588, 589, 593, 601, 602, 606, 607, 608, 609, 610, 615, 617, 618, 625, 626, 630, 632, 633, 637, 642, 643, 644, 645, 646, 1031, 1351, 1358, 1375, 1419, 1477, 1918, 1945, 1971, 1972, 1976, 2026, 2096, 2097, 2098, 2099, 2105, 2111, 2143, 2165, 2166, 2196, 2447, 2456, 2462, 2471, 2477, 2548, 2557, 2564, 2568, 2569, 2589, 2595]\n"
     ]
    }
   ],
   "source": [
    "print(\"visualizing where we have strong d or GOP lean and overuse\")\n",
    "DemVTDsToPatchDown = list()\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.1)\n",
    "    if vtdUse[v] > 1.15:\n",
    "        if vtdLean[v] < 0.3:\n",
    "            plotPoly(vtdGeom[v])\n",
    "            plotCenter(\"d\",vtdGeom[v],4)\n",
    "            DemVTDsToPatchDown.append(v)\n",
    "        elif vtdLean[v] > 0.6:\n",
    "            plotCenter(\"r\",vtdGeom[v])\n",
    "plt.show()\n",
    "print(\"The Dem districts leaning less than 30pct for Trump and use > 1.15 are\")\n",
    "print(DemVTDsToPatchDown)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "86c05beb-f21f-424d-a944-afb492015bc2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "if we patch all these overused blue districts to 1.0 usage, the statewide swing would be 0.9732080689838664 GOP fractional swing\n"
     ]
    }
   ],
   "source": [
    "swingSum = 0\n",
    "for v in DemVTDsToPatchDown:\n",
    "    swingSum += (vtdUse[v] - 1.)/float(nStateDistricts) * ( 0.5 - vtdLean[v])\n",
    "print(\"if we patch all these overused blue districts to 1.0 usage, the statewide swing would be\",swingSum,\"GOP fractional swing\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5e09d18f-7d8a-4fc2-9f32-5ed7ac72f6ca",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for v in DemVTDsToPatchDown:\n",
    "    plotPoly(vtdGeom[v])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20f382a2-cd7b-4f77-83e1-7533f6763a7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#consider a targeted patch down based on above -- only consider Dem districts to patch down.  May need to visualize districts where these are near HD boundary"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
